Full-Time
Engineering Senior Manager
Updated on 5/26/2026
xAI
1,001-5,000 employees
Generative AI chatbot leveraging real-time data
No salary listed
Memphis, TN, USA
In Person
Primarily onsite in Memphis area; relocation needed if not local; travel up to 15%
 Engineering Management (1) |
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- Bachelor’s degree in an engineering discipline.
- 7+ years of engineering experience.
- 2+ years in a direct people leadership role leading a team of engineers, contractors, technicians or other support staff.
- This role is primarily onsite at key project Memphis area locations and will require relocation if not local to the area.
- Must be willing to travel to other sites and/or visit vendors (up to 15%).
- Must be willing to work extended hours and/or weekends as needed.
- Lead the end-to-end engineering of physical infrastructure for xAI data centers and compute facilities, including structural and civil engineering (foundations, seismic design, site development, underground utilities), architectural engineering (facility layout, aesthetics, code compliance, and buildability), electrical systems (high-voltage, switchgear, UPS, generators, redundancy topologies), mechanical systems (HVAC, liquid cooling, chillers, CRAC/CRAH), controls & automation (BMS, SCADA, PLCs, monitoring), and high-capacity fiber optic networks (backbone, interconnects, and data hall connectivity).
- Build, mentor, and grow a high-performing multidisciplinary engineering team covering structural, civil, architectural, controls, electrical, mechanical, fiber infrastructure, and related disciplines.
- Develop and own technical standards, design guidelines, and best practices for power density, thermal management, structural integrity, seismic resilience, fiber performance and redundancy, uptime (targeting 99.999%+), efficiency (PUE/WUE optimization), and scalability to support massive GPU/accelerator clusters.
- Partner closely with construction, operations, procurement, and AI hardware teams to ensure seamless integration from design through commissioning, startup, and handover.
- Drive innovation in areas such as advanced liquid cooling, high-efficiency power delivery, intelligent controls, sustainable materials and design, optimized facility layouts, and high-bandwidth, low-latency fiber infrastructure to meet the extreme demands of next-generation AI training.
- Manage engineering budgets, schedules, risk assessments, and vendor relationships (OEMs, EPC firms, consultants, fiber providers) while maintaining aggressive timelines in a fast-paced environment.
- Enforce rigorous safety, quality, compliance, and reliability standards, including seismic design, structural integrity, redundancy requirements (N+1, 2N, etc.), architectural code compliance, fiber network resilience, and regulatory adherence.
- Provide technical leadership and regular updates to senior leadership on infrastructure roadmaps, performance metrics, lessons learned, and strategic recommendations.
- 7+ years of experience in physical infrastructure engineering for data centers, hyperscaler facilities, power plants, or other industrial projects.
- Deep expertise across multiple disciplines: structural and civil engineering, architectural engineering, electrical (power distribution, substations, backup systems), mechanical (cooling, HVAC, fluid systems), controls/automation, and fiber optic infrastructure for mission-critical environments.
- Experience leading the design and delivery of high-density compute infrastructure supporting AI, HPC, or similar workloads at massive scale, including robust fiber networking.
- Strong track record of building and leading technical teams, delivering complex projects on aggressive schedules and budgets, and solving ambiguous, high-stakes engineering challenges.
- Hands-on experience with relevant tools and standards (e.g., AutoCAD, Revit, ETAP, BIM, structural analysis software, fiber design tools, ASHRAE, IEEE, NFPA, IBC, Uptime Institute Tier standards, TIA-942).
- Ability to thrive in a high-velocity, high-ambiguity environment with a hands-on, continuous improvement mindset and exceptional problem-solving skills.
- Experience with liquid cooling systems, high-voltage power infrastructure for GPU clusters, advanced controls/BMS, large-scale structural/civil/architectural design, or high-capacity fiber networks for AI data centers.
- Background supporting hyperscalers, large AI training clusters, or similar power- and cooling-intensive environments with extensive fiber interconnects.
- Familiarity with fast-track design-build approaches, value engineering, sustainability practices, and integrated structural/architectural/fiber solutions in critical infrastructure.
- Professional Engineer license.
- Experience managing multimillion-dollar engineering scopes and cross-functional stakeholder alignment.
- Ability to work in industrial/data center environments and lead teams under pressure during phases.
xAI builds Grok, a generative AI chatbot with a Hitchhiker’s Guide-inspired persona that uses real-time data from X to produce current, culturally aware responses. Grok is accessible to premium subscribers on X, via a standalone website, mobile apps, and through an API for developers. The company also develops large-scale AI infrastructure, such as the Colossus supercomputer, to train and run its models. Its goal is to pursue truth-seeking AGI research and grow a capital-intensive platform that could support a major public offering in the future.
Company Size
1,001-5,000
Company Stage
Series E
Total Funding
$42.4B
Headquarters
Palo Alto, California
Founded
2023
Simplify's Take
What believers are saying
- Grok Build targets developers with terminal-native agentic coding workflows.[1]
- Screenshot pasting improves debugging for UI bugs and broken terminal outputs.
- Canva, Gamma, and Vercel connectors extend Grok into creator workflows.
What critics are saying
- EPA scrutiny and NAACP litigation threaten Memphis turbine operations supporting Colossus.
- Over fifty researchers reportedly left after SpaceX absorbed xAI, weakening execution.
- Grok's deepfake controversy invites regulation, app-store scrutiny, and enterprise buyer backlash.
What makes xAI unique
- Real-time X data gives Grok fresher context than static-dataset rivals.[1][3]
- Grok 4 combines native tool use with real-time search integration.[3]
- Colossus training infrastructure supports rapid model iteration at massive scale.[4]
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6 month growth
↑ 0%1 year growth
↑ 2%2 year growth
↑ 16%Grok Build runs coding agents at $1 in, $2 out. The catch is that xAI published zero benchmarks. xAI shipped its own terminal coding agent on May 14 and quietly listed the model behind it, grok-build-0.1, in the API on May 20. The rate is $1.00 input and $2.00 output per million tokens, which undercuts OpenAI's Codex model and lands at roughly a seventh of what Claude Opus 4.7 charges on output. The price is the easy part to write about. The hard part is that xAI shipped it with no SWE-Bench number, no coding eval, nothing. You are being asked to route real work to a model on price alone. The short of it. * Grok Build is the CLI (announced May 14, sold through a SuperGrok subscription). grok-build-0.1 is the API model behind it, listed May 20 at $1.00 in, $0.20 cached, $2.00 out, 256K context. * A 500K-input, 80K-output coding task runs $0.66 on it, against $2.00 on OpenAI's Codex model and $4.50 on Claude Code with Opus 4.7. For agents, output price is the whole game. * xAI published no benchmarks. None at all. The cheap rate comes with a real question mark on quality. Grok Build the CLI is not grok-build-0.1 the model. Most of the coverage conflates these, so it is worth pulling them apart before any pricing makes sense. On May 14 xAI announced Grok Build, a command-line coding agent. It plans before it edits, shows clean diffs, runs subagents in parallel git worktrees, has a headless mode for automation, and reads your existing AGENTS.md, MCP servers, hooks, and skills without conversion. If that description sounds like Claude Code or the Codex CLI, that is the point. xAI built it to be a drop-in for developers already using one of those. The CLI itself is distributed through a subscription, not metered per token. Press coverage puts the SuperGrok Heavy tier that includes it around $299 a month, with a discounted intro rate, but those figures come from reporters, not from xAI's own page, so treat them as approximate. Six days later, on May 20, the model that powers it showed up in the pay-as-you-go API as grok-build-0.1. That is the one with a rate card, and the one that matters if you are wiring it into your own agent instead of using xAI's CLI. One odd detail: the model page lists grok-build-0.1 with grok-code-fast-1 aliases, which means it is the evolution of xAI's existing coding line rather than a from-scratch first model. Do not let anyone tell you it is xAI's first coding model. It is the rebrand of one they already had. The rate card next to its rivals. Here is what the model behind each major coding agent costs per million tokens, pulled from each provider's own pricing page. | Model | Input / 1M | Cached / 1M | Output / 1M | Context | | grok-build-0.1 | $1.00 | $0.20 | $2.00 | 256K | | grok-code-fast (predecessor) | $0.20 | - | $1.50 | 256K | | gpt-5.3-codex | $1.75 | $0.175 | $14.00 | 272K | | Claude Sonnet 4.6 | $3.00 | $0.30 | $15.00 | 1M | | Claude Opus 4.7 | $5.00 | $0.50 | $25.00 | 1M | Two things stand out. First, on output, the number that drives coding-agent bills, grok-build-0.1 at $2.00 is 7x under gpt-5.3-codex and 12.5x under Opus 4.7. Second, xAI undercut itself in a confusing way: the older grok-code-fast model it is built on is cheaper on both input and output. If raw cost is all you care about and you do not need whatever grok-build-0.1 added, the predecessor is still the bargain. What a real coding task costs. Rate cards lie about coding agents because the input-to-output ratio is so lopsided. An agent reads a lot and writes less, but the writes are where the expensive output tokens land. Take one concrete task: an agent ingests roughly 500K tokens of context (a medium repo, the relevant files, a few iterations of reading) and produces 80K tokens of output (a feature plus the diffs, tests, and explanation). Here is the bill on each. | Coding agent | Model | Input cost | Output cost | Task total | | Grok Build | grok-build-0.1 | $0.50 | $0.16 | $0.66 | | OpenAI Codex | gpt-5.3-codex | $0.88 | $1.12 | $2.00 | | Claude Code (Sonnet) | Sonnet 4.6 | $1.50 | $1.20 | $2.70 | | Claude Code (Opus) | Opus 4.7 | $2.50 | $2.00 | $4.50 | Grok Build comes in at $0.66. Codex bills three times that for the identical task, Claude Code on Sonnet a bit over four times, and Opus nearly seven. Run a hundred of those tasks a month and you are choosing between a $66 invoice and a $450 one on Opus. That is real money for a team running agents at volume, and it is the entire reason anyone will look at this model despite the missing benchmarks. Caching widens the gap, then narrows it. Coding agents re-send the same context on every turn: the system prompt, the file tree, the files already in view. Prompt caching is what keeps that from bankrupting you. Take a heavier session, say 3M input tokens across forty turns with 70% landing as cache hits, plus 400K output. grok-build-0.1 runs about $2.12, gpt-5.3-codex about $7.54, and Opus 4.7 about $15.55. The output price still dominates, so Grok Build holds its lead. One nuance worth flagging if you are input-bound rather than output-bound: on cache hits alone, gpt-5.3-codex at $0.175 is fractionally cheaper than grok-build-0.1 at $0.20, and Anthropic's 10x cache discount brings Opus reads down to $0.50. xAI's cache discount is shallower (5x, not 10x). So a workload that is almost all cached reads and very little generation closes the gap more than the headline numbers suggest. The further your task tilts toward output, the more Grok Build wins. The number xAI did not publish. This is where the post would normally have a benchmark table. It does not, because xAI has not given TokenCost one. The official announcement has no scores. The model page has no scores. Benchmark trackers list grok-build-0.1 with zero sourced results. For a model whose entire pitch is coding, shipping with no SWE-Bench Verified number is a conspicuous silence. You will see numbers floating around anyway. Ignore them unless they cite xAI directly. The only legitimate coding score in this lineage belongs to grok-code-fast-1, the predecessor grok-build-0.1 is aliased to, and that model sat in the 57 to 70 percent range on SWE-Bench Verified depending on the harness, well short of the high 80s that Opus 4.7 and GPT-5.5 post. If grok-build-0.1 is a meaningful step up from that, xAI has not said by how much. TokenCost has not put grok-build-0.1 through its own harness yet, and that is rather the point: almost nobody has. The early hands-on writeups, like Kilo's teardown, are still feeling out where it breaks. So the honest read is this: a cheap coding model from a lab with a real track record, unproven on any public eval. Cheap and unproven is a fine bet for low-stakes, high-volume work where a wrong answer costs you a retry. It is a bad bet for the autonomous, merge-without-review agent you point at a production codebase. Until xAI publishes, the price tag is the only hard data point you have. Who should actually switch. If you run a fleet of coding agents on bulk, forgiving work, such as mass refactors, test generation, doc updates, or first-draft PRs that a human reviews, the 3x to 7x cost gap is hard to ignore. Wire grok-build-0.1 into a router, send it the cheap-to-retry traffic, and keep your eval harness watching the diff quality. The downside of a bad output is a re-run, and you are paying a fraction per run. If you are shipping autonomous agents against production code, or you need the last several points of SWE-Bench accuracy, stay where you are. Opus 4.7 and gpt-5.3-codex cost more because, on the evidence TokenCost actually have, they earn it on the hardest coding tasks. Grok Build has not shown it can hang there, and finding out the expensive way on a live repo is not worth saving a few dollars per task. To model this against your own input/output mix, the calculator runs the math for any token split, and the pricing page lists every coding model side by side. For the broader xAI rate picture, see the Grok 4.3 Colossus 2 piece, and for the rival agents, the Claude Code vs Codex cost breakdown. Sources. * xAI: Introducing Grok Build - May 14, 2026 CLI announcement, features, distribution * xAI: grok-build-0.1 model page - 256K context, grok-code-fast-1 aliases, above-200K rate note * xAI: API pricing - $1.00 input, $0.20 cached, $2.00 output; Grok 4.3 $1.25/$2.50 * OpenAI: API pricing - gpt-5.3-codex $1.75/$14.00, GPT-5.5 $5/$30 * Anthropic: Claude pricing - Opus 4.7 $5/$25, Sonnet 4.6 $3/$15, 10x cache discount * OpenRouter: grok-build-0.1 - May 20, 2026 API listing date corroboration
Musk's xAI is being sued over its data center generators - now it's buying $2.8B more. 1 hour ago · Elon Musk's xAI has gotten itself in hot water over its use of polluting generators at its data center near Memphis, Tennessee. Now it wants to buy even more of them. In SpaceX's IPO filing, released Wednesday, the company said its xAI division will buy another $2.8 billion worth of turbines for its AI infrastructure over the next three years. One deal, worth $2 billion, is specifically for "mobile gas turbines," the kind that it's currently being sued over. The NAACP filed a lawsuit against xAI last month for operating dozens of unregulated gas turbines that worsen the air quality in one of the most polluted parts of the country. The organization has sought an injunction against xAI's use of the turbines. So far, xAI has been granted permits for 15 turbines. As of a few weeks ago, it was using 46. Each of the types of turbines xAI is operating have the potential to emit more than 2,000 tons of NOx pollution annually, a group of chemicals that contributes to asthma-inducing smog. The company claims that it can operate the turbines for up to a year without permits because they are "mobile" - that is, they're still on the trailer they were shipped on. The company appears to be exploiting a discrepancy between state and federal interpretations. Mississippi claims it doesn't need to permit mobile generators. But federal regulations say that turbines of that size, even if they're on a trailer, are still subject to air-pollution regulations. The EPA ruled earlier this year that xAI was operating the turbines in violation of federal law. SpaceX acknowledges the risks in its IPO filing. "We currently rely significantly on natural gas and gas turbine technology to power our data center operations," it wrote. Injunctions or rescinded permits "would adversely affect our AI business." This editorial summary reflects Tech Crunch and other public reporting on Musk's xAI is being sued over its data center generators - now it's buying $2.8B more.
Latest xAI developments: API expansion and the cost challenge of AI growth. April 23, 2026 Artificial intelligence continues to evolve at a rapid pace, and xAI is among the companies making significant moves in both technology and business strategy. Recent updates show a clear push toward expanding its API ecosystem while also addressing the growing financial demands of large-scale AI development. API enhancements driving commercial growth. xAI has introduced new API improvements designed to strengthen its position in the developer and enterprise market. These updates focus on: * Improving access to advanced AI models for developers * Expanding integration capabilities for business applications * Enhancing scalability for enterprise-level usage * Supporting more flexible and efficient AI deployment This direction highlights a strategic shift from research-focused development toward a more structured commercial platform. By strengthening its API offerings, xAI is positioning itself to attract businesses looking to integrate advanced AI into their workflows. Increasing pressure from development costs. Despite rapid innovation, the financial demands of artificial intelligence development remain extremely high. Training and maintaining large-scale AI systems requires: * Significant investment in high-performance computing infrastructure * Continuous scaling of data centers and GPU resources * High operational and energy costs * Ongoing research and model improvement expenses While revenue opportunities are growing, they are still being challenged by the speed and scale of these expenses. This imbalance is not unique to xAI but reflects a broader industry trend across leading AI companies. The industry shift toward sustainability. Across the AI sector, companies are now focusing on long-term sustainability. The emphasis is shifting from rapid model development alone to building platforms that can generate stable revenue through: * Enterprise subscriptions and API usage * Cloud-based AI services * Developer ecosystems and integrations * Scalable infrastructure monetization xAI's recent updates reflect this broader industry direction, where profitability and infrastructure efficiency are becoming just as important as model performance. Conclusion. xAI's latest developments demonstrate a dual focus: expanding its technical capabilities while addressing the economic realities of large-scale AI systems. As the industry matures, companies that successfully balance innovation with sustainable business models are likely to lead the next phase of artificial intelligence growth.
Lawsuit launched against Musk's xAI over 'illegal' gas turbines at Memphis data center. "A data center should not be a potential death sentence on a community's health" April 15, 2026 Campaigners have formally launched a lawsuit against Elon Musk's xAI, claiming gas turbines at its data center in South Memphis are being operated illegally. Civil rights organization the NAACP has made a complaint against xAI, and its subsidiary MZX Tech, alleging that 27 methane gas turbines that power the company's Colossus 2 data center are being run in violation of the Clean Air Act. xAI has been operating data centers in Memphis and the surrounding area since 2024, using gas turbines to power the facilities. xAI's Memphis data centers - Google Maps "The company's failure to get a permit for its power plant - which is located near homes, schools, and churches - creates added health risks for families in North Mississippi and Memphis and is a clear violation of the Clean Air Act, which requires major sources of pollution to obtain air permits before being constructed or operated," a statement from NAACP said. "A data center should not be a potential death sentence for a community's health. By looking to evade clear air laws to operate dirty turbines that emit pollution and known carcinogens, these companies are following a shameful, familiar pattern: asking black and frontline communities to bear the toxic brunt of 'innovation'," said Abre Conner, NAACP director of environmental and climate justice. "As we shared since xAI started operating in Memphis, our homes, churches, and playgrounds will not be sacrifice zones for Big Tech's convenience. The NAACP stands firm that true progress cannot be built by ignoring community health and our environment. Our right to clean air is not up for negotiation, especially when companies prove expediency, not people, is their priority." The NAACP claims xAI's power plant in Southaven has the potential to emit more than 1,700 tons of polluting nitrogen oxides (NOx) each year. The turbines also have the potential to release up to 180 tons of fine particulate matter, 500 tons of carbon monoxide, and 19 tons of formaldehyde - a toxic, cancer-causing chemical - each year. The Southern Environmental Law Center and Earthjustice are representing the NAACP in the case. "xAI's continued operation of these turbines without a permit and without adequate pollution controls is not only illegal, it's an insult to families living nearby who for months have expressed serious concerns about how air pollution from the company's personal power plant could impact their health and well-being," SELC senior attorney Ben Grillot said. "xAI must be held accountable for its reckless, unlawful actions - and that's exactly what this lawsuit aims to do." News of the lawsuit, which will be heard in the district court of Northern Mississippi, first emerged in February. xAI uses its data centers in Tennessee and Mississippi to power its Grok AI chatbot. The company came to Memphis in 2024, launching its Colossus supercomputer in a new data center housed in a former Electrolux factory in Memphis's Boxtown district. It purchased the site for Colossus 2 last March, and the data center came online in January. Despite Musk claiming it offered 1GW of capacity at launch, satellite imagery taken in January reportedly showed it had cooling equipment installed capable of managing 350MW. A third data center is in the works, located in Southaven, across the state border in Mississippi, and the company is also spending $659m on another building to be constructed on an adjacent land parcel. Musk says his company, which is now part of SpaceX, will eventually have access to 2GW of compute power from the cluster, and gas turbines will be key to supplying this. In March, it received permission to install 41 new turbines to power its data centers. News of the lawsuit comes a week after it was reported that work on a water recycling plant in Memphis, being constructed by xAI, has ceased. The company had heralded the $80 million project as a key community benefit for the city, claiming the facility would clean up dirty water for use in xAI's data centers, as well as other businesses. But local news outlet the Daily Memphian reported that work on the project is currently on "indefinite pause", with staff redirected to other sites. In response, Musk posted on his social media network X, stating: "We need to focus on finishing Colossus 2 and ensuring it is extremely stable, then we will build the water recycling plant." DCD has contacted xAI for comment on the lawsuit. More in North america.
The NAACP has sued Elon Musk's xAI, alleging Clean Air Act violations from the company's use of natural gas-burning turbines to power data centres in Memphis, Tennessee, and Southaven, Mississippi. The lawsuit, filed in the US District Court for the Northern District of Mississippi, claims xAI and its subsidiary MZX Tech installed and operated 27 gas turbines between August and December 2025 without proper permits. The turbines emit smog-forming pollutants and particulate matter that pose health risks to nearby residents. xAI operates the Colossus 1 and 2 data centres in Memphis and is building additional facilities in Southaven. The NAACP seeks to halt operations until proper permits are obtained and pollution controls applied. Now owned by SpaceX, xAI is expanding its data infrastructure to compete with OpenAI, Anthropic and Google.