Lead Engineer - AI Engineering
About the job
- Proficiency in Python and/or JavaScript, TypeScript, Node.js, Java, or Go, with strong coding and software engineering practices.
- Expertise with AI/ML libraries and frameworks such as LangChain, OpenAI APIs, PyTorch, TensorFlow, and commercial or open-source large language models.
- Hands-on experience with large language models, prompt engineering, and natural language processing.
- Knowledge of agent orchestration platforms and multi-agent systems, including AutogenAI, LangGraph, and the MCP protocol.
- Familiarity with data management, vector databases, semantic retrieval, and real-time data pipelines.
- Experience deploying AI systems on cloud platforms such as Amazon Web Services or Google Cloud, with container orchestration using Docker and Kubernetes.
- Strong understanding of machine learning model training, fine-tuning, and evaluation techniques.
- Awareness of AI ethics, data privacy, and secure handling of sensitive information.
- A master's degree in Computer Science, AI/ML, Engineering, Mathematics, or a related field.
- At least 3 years of relevant experience.
- Thorough experience in AI and generative artificial intelligence application development and deployment, particularly with autonomous agent systems or related AI software engineering roles.
- Demonstrated ability to work independently in fast-paced, experimental environments.
- Hands-on experience designing and building generative artificial intelligence applications supporting agent orchestration, multi-step reasoning, prompt engineering, retrieval-augmented generation integration, and model selection.
- Expertise with large language models and deep learning models, machine learning lifecycle management, data generation methods, model training and validation, software engineering, and system architecture.
- Must be willing to work from the office located in Bangalore.
- Must be 18 years or older.
- Must submit an employment application through the GE Vernova careers page.
- Design, implement, and optimize AI agents using large language models, reinforcement learning, planning algorithms, and decision-making frameworks.
- Develop scalable multi-agent architectures supporting long-horizon reasoning, autonomy, planning, interaction, and complex task completion.
- Integrate AI agents with application programming interfaces, backend services, databases, and enterprise applications.
- Prototype, deploy, and maintain AI-driven systems, ensuring reliability and performance in production environments.
- Optimize agent behavior through continuous feedback, reinforcement learning, and user interaction.
- Collaborate with research, engineering, product, and deployment teams to iterate on agent capabilities.
- Monitor AI agent performance, conduct rigorous evaluations, implement safety guardrails, and ensure ethical artificial intelligence practices.
- Document AI agent architectures, design decisions, workflows, and technical documentation.
- Stay current with emerging AI technologies, contribute to platform and tooling improvements, and share knowledge within the team.
- Design and implement large-scale artificial intelligence and machine learning solutions integrating state-of-the-art research into global products.
About the company
GE Vernova makes equipment and software that generate and manage electricity for utilities, power producers, and industrial customers. Its Power, Wind, and Electrification businesses span gas turbines, wind generation, and the systems that move electricity across grids. The company supplies generators, grid equipment, and controls, while its software coordinates network operations and integrates changing sources of power. Customers buy equipment and enter service agreements for maintenance, upgrades, and technical support over its operating life, alongside purchases of software and related services. GE Vernova became an independent company in 2024 after separating from GE and is headquartered in Cambridge, Massachusetts.
Company Size
10,001+
Company Stage
N/A
Total Funding
$17.6M
Headquarters
Cambridge, Massachusetts
Founded
2024
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Simplify's Take
What believers are saying
- Demand supports expansion: July 2026 results show GE Vernova booked $24.2 billion of quarterly orders, up 88% organically.
- Service commitments support recurring work: GE Vernova says services account for more than 55% of its backlog.
- Graduates build depth through rotations: GE Vernova runs two-year Next Gen development programs in engineering, technology, and operations.
What critics are saying
- Wind remains a drag: July 2026 results show GE Vernova lost $275 million in quarterly Wind segment EBITDA.
- Project margins absorb overruns: GE Vernova locks prices before completion and discloses meaningful expenses from excess costs and penalties.
- Field assignments demand long weeks: GE Vernova's listed transformer specialist works typical 12-hour site days, up to six weekly.
What makes GE Vernova unique
- Its technology underpins global power: GE Vernova says customers generate approximately one-quarter of world electricity using its equipment.
- Gas turbine scale anchors expertise: GE Vernova reports the largest installed fleet by generating capacity, across approximately 7,000 turbines.
- Nuclear work reaches beyond equipment: GE Vernova Hitachi supplies advanced reactors, fuel, and services for operating plants.
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Benefits
Health Insurance
Dental Insurance
Vision Insurance
Life Insurance
Disability Insurance
401(k) Retirement Plan
401(k) Company Match
Paid Vacation
Paid Parental Leave
Mental Health Support
Relocation Assistance
Performance Bonus
Company News
Jim Cramer highlighted GE Vernova and Vertiv on 2 October, noting their exposure to data centre growth. He questioned why the jobs report didn't reflect the data centre buildout, suggesting commercial construction is weak whilst data centre projects remain strong. Vertiv's Q2 net sales grew 24% annually, with operating profit up 44%. However, revenue growth of 17.8% missed analyst estimates of 23.6% due to supply chain issues, raising concerns about backlog conversion. The company's capital expenditure surged 285% to $173 million. GE Vernova's shares have risen over 240% since October 2024. Q2 customer downpayments generated a $6.4 billion working capital benefit, pushing free cash flow up 2,532% to $5.1 billion. The company raised its full-year cash flow guidance to $11.5–$12.5 billion from $6.5–$7.5 billion.
General Electric spun off its energy division as GE Vernova on 2 April 2024. The stock opened at $142.25 per share and reached a record high of $1,174.86 on 30 June 2026, now trading at about $1,000. GE Vernova operates three segments: Power, Electrification, and Wind. Strong demand from cloud and AI markets drove growth in its Power and Electrification businesses, whilst the Wind segment faced operational challenges. The company's backlog grew 37% year-over-year to $176.3 billion at the end of Q2 2026. Analysts expect revenue and adjusted EBITDA to grow at compound annual growth rates of 17% and 60% respectively from 2025 to 2028. GE Vernova trades at 27 times next year's adjusted EBITDA, with an enterprise value of $262 billion.
GE Vernova, General Electric's former energy division spun off in 2024, is positioned to benefit from surging power demands at AI data centres. The company operates three segments: Power (55% of 2025 orders), Electrification (33%), and Wind (13%), providing turbines, transformers, and grid services. Orders grew 24% organically in the first half of 2026, driven by Power and Electrification segments. By Q2 2026, GE Vernova's backlog reached $176.3 billion — 4.6 times its 2025 revenue of $38.1 billion. The company expects 2026 revenue to grow 20-22%, accelerating from 9% growth in 2025 and 5% in 2024. Fortune Business Insights projects the global AI in power utilities market could expand at a 19.3% compound annual growth rate from 2026 to 2034.
Four major engineering firms have signed a memorandum of understanding to cooperate on building and deploying small modular reactors (SMRs) in Europe. GE Vernova, Hitachi, Samsung C&T, and Poland-based SGE will work together on market development and commercial opportunities for the BWRX-300, an SMR developed by GE Vernova and Hitachi subsidiaries. The agreement was signed during the Atlantic Council Nuclear Energy Policy Summit at the UN General Assembly in New York. SMRs are smaller-scale, plug-and-play nuclear generators that are cheaper and quicker to construct than traditional nuclear plants. They use low-enriched uranium that can be sourced entirely from western enrichment providers. The initiative has government backing from the US, Japan, and South Korea, supported by a trilateral agreement signed at the recent NATO summit.
GE Vernova shares have fallen 20.8% from their 52-week high of $1,195.94, closing at $946.22 on 21 September. Despite the pullback, the stock remains up 47% over the past year. The company reported strong second-quarter results, with orders of $24.2 billion, up 88% organically year-on-year. Revenue reached $11.1 billion, up 22%, whilst net income for the first six months totalled $5.3 billion, compared with $756 million in the prior-year period. GE Vernova is positioned to benefit from surging power demand driven by artificial intelligence data centres. The company also has a nuclear energy division developing small modular reactors through a joint venture with Hitachi, with commercial operation expected by the end of 2030. The company faces challenges including a forward price-to-earnings ratio of 38.1 and declining wind division sales.