Agent Strategist - Agent Development
About the job
- Communicate clearly, directly, and persuasively with technical and non-technical audiences.
- Use strong analytical and critical-thinking skills to break down complex problems, identify risks early, and adapt to changing circumstances.
- Engage with technical concepts, including reading API documentation, understanding data models and system architecture, and following engineering tradeoffs in design discussions.
- Have a track record of running multiple complex, high-visibility projects simultaneously and driving them to outcomes.
- Speak Spanish.
- A degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience, and/or an MBA or comparable experience at the intersection of technology and business is preferred.
- Own the agent development life cycle, taking agents from initial scope through conversation design, tooling, and evaluation to launch and continuous production iteration; translate business goals into agents that outperform and continually tune them based on real-world results.
- Advise enterprise leaders, understand their business success criteria, and shape the AI strategy to achieve them.
- Partner with customer working teams by running working sessions, troubleshooting agent issues, and making decisions that keep development on track for launch.
- Surface unmet customer needs and relay them to research and platform teams to influence product direction.
- Experience building or deploying AI/LLM agents in production, including hands-on work with evaluation frameworks, agent tooling, retrieval-augmented generation, or prompt engineering, in collaboration with technical counterparts.
- Experience as a founder, founding team member, or operator, balancing craft, ownership, and speed.
About the company
Sierra builds AI agents that handle customer conversations for businesses, from answering support questions to guiding purchases and managing account requests. Companies deploy the same agent across voice, chat, email, and messaging channels, with behavior shaped by their brand guidelines and business policies. Its Ghostwriter tool creates and updates agents from plain instructions or existing company materials, then tests changes before teams approve them. The platform connects agents to business systems so they take action, and Sierra charges for completed outcomes rather than the AI tokens consumed. Sierra was founded in 2023 and is headquartered in San Francisco, California, United States.
Company Size
1,001-5,000
Company Stage
Series E
Total Funding
$1.6B
Headquarters
San Francisco, California
Founded
2023
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Simplify's Take
What believers are saying
- Demand supports expansion: Sierra reported over $150 million in annual recurring revenue in February 2026.
- Sales reach expands: September 2026's OpenAI marketplace partnership lets eligible customers spend existing commitments on Sierra.
- New graduates gain customer exposure: Sierra's early career program pairs direct agent building with mentorship.
What critics are saying
- Sierra carries model cost exposure: Horizon customers pay for outcomes, while Sierra bears token spending.
- Expect regular office attendance: Sierra says employees spend most working time together in person.
- Customer emergencies interrupt planned work: Sierra says everyone drops everything when a customer has an issue.
What makes Sierra unique
- Enterprise software veterans lead Sierra: Taylor ran Salesforce, while Bavor led Google Labs.
- Payments bypass the AI model: Sierra routes card details directly to processors through separate secure infrastructure.
- Independent testing recurs: Sierra's AIUC-1 certification requires quarterly technical evaluations and annual audits.
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Benefits
Unlimited Paid Time Off
Medical, Dental, and Vision benefits for you and your family
Life Insurance
Disability Insurance
401(k) Company Match
Parental Leave
Fertility Treatment Support
Discretionary Benefit Stipend
Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↓ -17%2 year growth
↓ -3%Meta & NiCE back AI agent protocol for customer service. Wed, 7th Oct 2026 (Today) Meta has previewed the Personal Agent Protocol, an open standard for interactions between consumers' AI agents and businesses. NiCE is co-developing the protocol with Meta, Sierra and other industry partners. The proposal outlines how a customer's personal AI agent can find a business, authenticate itself and act on the customer's behalf. It offers an early indication of how companies may need to handle a growing volume of requests initiated by software agents rather than people. According to NiCE, the standard is intended to address a series of operational questions for customer service teams, including how businesses verify which customer an agent represents, what the agent is allowed to do and how those interactions are managed across automated systems and human staff. It also points to a shift in demand patterns. Rather than reducing service volumes, personal agents could increase them by pursuing tasks customers might otherwise abandon, such as repeated follow-up questions, refund requests or booking changes. "Personal AI agents have endless time that consumers don't, and that brings a new era of growth for customer service. Customers' agents can sign in, ask follow-up questions on their behalf and get to resolution faster, which means more demand, more persistence and higher expectations. An open standard is how that demand reaches businesses with trust, and NiCE is proud to shape what comes next alongside Meta and others. Companies that compete every day agreeing on a standard so customers and enterprises both benefit is the industry at its best. Personal agents bring customers to the door, and resolution brings them back," said Scott Russell, Chief Executive Officer, NiCE. How It Works Under the proposed approach, a company would publish information at a known digital address telling personal agents where to sign in and which interfaces they can use. The protocol is designed so an agent can discover that information in a single request before continuing the interaction across application programming interfaces, web pages or conversational channels. NiCE said the model also relies on customer-specific authentication tokens, with access limited according to the business's own rules. That structure is intended to let companies decide which personal agents they will accept, what those agents may do and when a person should take over a case. Philipp Heltewig, Chief AI Officer at NiCE, said the protocol creates a common language between a customer's software agent and a company's systems. "Personal agents already work for consumers, and today a customer's agent and a company's agent share a common language. When a customer's agent arrives with a goal, like a refund or a rebooked flight, the business's AI agent checks who it represents and what it is allowed to do, then works the request to resolution using the systems the business already runs on. When the case needs judgment, a person joins the same conversation with the full context, and every reply says who is responding. That is AI agents and people working as one crew, with clear jobs, shared context and a clean handoff. Enterprises decide which agents they serve, what access those agents get and when a person steps in, and now the conversation turns to what we build with it," said Heltewig. Operational Pressure For contact centre operators and IT teams, the prospect of machine-driven customer requests raises questions not just about access, but also scale. Traditional service models have been built around human behaviour, where delays, drop-offs and limited persistence naturally constrain demand. Personal agents could change that pattern by sending requests at machine speed and continuing interactions without the time limits of a human customer. That would require businesses to think not only about external connections to personal agents, but also about internal routing between AI systems, workflows and staff. Neeraj Verma, Vice President, Agentic AI, NiCE, said the proposed design aims to keep those interactions consistent while preserving business control. "What I like about the Personal Agent Protocol is how much it solves with a simple design. A company publishes one document at a well-known address that lists its sign-in endpoints and interfaces, so an agent finds everything in a single request. Each personal agent gets its own token for each customer, with access scoped to what the company allows, and that same token works across APIs, web pages and conversations, so the experience stays consistent from first request to resolution. Every reply says whether an AI agent or a person is responding, and when a case calls for judgment, a person joins the same conversation with full context. Enterprises keep control throughout: they set which agents they serve, what access those agents get and when a person steps in," said Verma. The initiative comes as businesses across customer service, digital operations and enterprise software examine how personal AI assistants could change online interactions, particularly in sectors where identity, permissions and audit trails are central to the transaction. For companies preparing for that shift, the protocol suggests the challenge will extend beyond opening a technical connection. They will also need systems that can distinguish between customers, agents and staff at each stage of an interaction, while handling a potentially much higher volume of service requests than today.
Sierra announces Personal Agent Protocol, an open standard for personal AI agents. Personal Agent Protocol is built on OAuth, lets a business decide whether an agent reaches it through a website, an API or an agent of its own, and arrives with Stripe and Shopify as partners, both of which have already joined a rival protocol run by Visa October 6, 2026 - 7:43 pm Sierra and Meta are developing Personal Agent Protocol, an open standard defining how personal AI agents authenticate with businesses and what those businesses let them do, with Genesys, Instinct, Rocket, Shopify, Stripe and Walmart. A v0.1 specification is due this month, and payments are listed as a future extension rather than part of it. Meta and Sierra are writing a standard for how personal AI agents talk to businesses. Stripe and Shopify are among the partners. Both have already joined a rival protocol run by Visa. Personal Agent Protocol is meant to handle authentication and show companies what agents are doing on their sites, Sierra said in a post by Bret Taylor and Clay Bavor. The other partners named are Genesys, Instinct, Rocket and Walmart. A v0.1 specification is due later this month. Sessions are built on OAuth. An agent can start as a guest to check stock or a returns policy, and once a customer signs in they decide whether it gets read-only or write access. The session carries across channels, so a question asked before signing in and an order changed afterwards belong to one visit. The company chooses whether the agent works through its website, through its APIs using standards such as MCP and OpenAPI, or through an agent of its own. We reported in June that Visa had plugged into ChatGPT so agents could buy from about 175 million merchants, under a Trusted Agent Protocol that Microsoft, Stripe, Shopify and Worldpay had already joined. Stripe and Shopify are now in both. Rocket's statement names Meta's Muse agent moving across its platform from finding a home to arranging the financing. Muse launched four weeks ago and pays using saved cards through Stripe's Link. The agents are arriving faster than the arrangements they will work under. Hark released an agent this morning that buys groceries, books cars and pays bills, a year before its hardware is due. All of them reach Europe eventually. A payment approved by software on somebody's behalf has no carve-out from strong customer authentication, which was written for a person approving a transaction tied to a named payee and an amount. Sierra lists payments as a future extension rather than part of the first specification. Push notifications and more detailed permissions are also future work. One partner has a European headquarters, and it is Stripe, which runs dual headquarters in San Francisco and Dublin. No European retailer, bank or payment company has been named as joining.
Meta and Sierra launch open Personal Agent Protocol with Stripe, Walmart. Phemex News 2026/10/06 11:51 Meta and AI startup Sierra have jointly launched the Personal Agent Protocol, an open standard designed to govern how personal AI agents interact with businesses. Founding partners include major industry players such as Stripe, Walmart, Shopify, Genesys, Instinct, and Rocket. The protocol utilizes OAuth-based authentication, enabling users to grant agents specific read or write access to their accounts while allowing businesses to independently control exposed features and monitor agent activity via websites, APIs, or proprietary agents. The v0.1 specification is scheduled for release later in October. Disclaimer: The content provided on Phemex News is for informational purposes only. Phemex do not guarantee the quality, accuracy, or completeness of the information sourced from third-party articles. The content on this page does not constitute financial or investment advice. Phemex strongly encourage you to conduct you own research and consult with a qualified financial advisor before making any investment decisions.
Cigna reaffirms 2026 outlook, targets complex care and ai-driven growth. September 30, 2026 Key points. * Cigna reaffirmed its 2026 adjusted EPS guidance of at least $30.45 and maintained its target for 10%-14% annual adjusted EPS growth through 2030, supported by operating growth and capital deployment. * The company is prioritizing complex care, personalization and AI, citing tools that have reduced customer calls, clinical documentation time and specialty-benefit review times. Partnerships with Sierra AI and OpenAI will initially focus on conversational healthcare tools and oncology. * Specialty and Care Services is expected to be Cigna's main growth engine, with 8%-12% annual earnings growth through 2030 and more than 40% of company earnings by then. Cigna also plans a $3 billion efficiency initiative and is shifting its pharmacy-benefit business toward a fee-based model. * Interested in Cigna Group? Here are five stocks we like better. Cigna Group NYSE: CI reaffirmed its 2026 outlook and outlined a long-term strategy centered on complex care, technology-enabled personalization and disciplined capital deployment at its 2026 Investor Day. President and CEO Brian Evanko said the company has reshaped its portfolio over the past decade from a predominantly employer-focused health plan into three growth platforms: Evernorth Specialty and Care Services, Evernorth Pharmacy Benefit Services and Cigna Healthcare. He said the company has reduced exposure to businesses where it lacked a competitive advantage, including its Medicare operations, while expanding specialty pharmacy and complex-care capabilities. The company reaffirmed its 2026 adjusted earnings-per-share guidance of at least $30.45. CFO Ann Dennison said that level would represent a 14% compounded annual growth rate over the past decade. Cigna also reiterated its target for 10% to 14% average annual adjusted EPS growth through 2030, including 6% to 9% operating-income growth and 4% to 5% annual EPS accretion from capital deployment. Focus on complex care and personalization. Evanko introduced the company's "Lead to One" strategy, which aims to deliver personalized healthcare support at scale. The approach is intended to serve members across the health continuum, from preventive care to individuals with chronic and complex conditions. According to Evanko, 8% of patients have complex care needs but account for 55% of healthcare spending. Cigna said all spending within its Specialty and Care Services business is tied to complex conditions, while approximately 55% of spending it manages in Cigna Healthcare and 70% of spending in Pharmacy Benefit Services is associated with complex care. The company said its Health Intelligence Engine combines medical, pharmacy, behavioral-health and other data with clinical expertise, analytics and artificial intelligence to identify risks and guide personalized actions. Chief Data, Digital and AI Officer Katya Andresen said current AI applications have reduced phone calls per customer by 20% over the past several years, reduced clinical documentation time at MDLIVE by up to 90%, and shortened a specialty benefit-review process from 15 minutes to 21 seconds. Discover more Stock market analysis Market cap calculator Cigna also highlighted a partnership with Sierra AI for conversational and agentic AI capabilities, as well as a recently announced collaboration with OpenAI focused on clinical AI. Chief Medical Officer Dr. Amy Flaster said the OpenAI work initially will focus on oncology through tools embedded in Accredo and Cigna Healthcare offerings. She emphasized that AI will augment rather than replace clinicians' judgment. Specialty services expected to drive growth. Matt Perlberg, president of Evernorth Pharmacy and Care Delivery, said specialty drugs represent a roughly $480 billion market growing at a high-single-digit rate. He said Evernorth's specialty ecosystem serves more than 1 million patients and generates more than $100 billion in annual revenue. Accredo, the company's specialty pharmacy, produces approximately $80 billion in annual revenue and handles more than 8 million specialty prescriptions annually, Perlberg said. About 40% of Accredo revenue comes from sources outside Cigna and Express Scripts, he added. The company cited access to more than 330 limited-distribution drugs, including more than 30 products exclusively available through Accredo. CuraScript, Evernorth's specialty-distribution business, generates about $25 billion in annual revenue and has grown roughly 20% annually over the past five years, Perlberg said. Cigna expects Specialty and Care Services to deliver 8% to 12% annual earnings growth through 2030, represent more than 40% of company earnings by that year and add about $20 billion in new distribution revenue. PBM model shifts toward fee-based structure. Adam Kautzner, president of Evernorth Care Management and Express Scripts, said Pharmacy Benefit Services manages $140 billion annually, serves 117 million Americans and expects to process more than 2 billion prescriptions in 2026. The business is transitioning to Evernorth Signature, a rebate-free, fee-based pharmacy-benefit model that Cigna said is designed to provide upfront patient discounts, greater client transparency and a flat administrative fee not tied to drug costs. The company plans to launch Signature for Cigna Healthcare's fully insured business in 2027, with commercial clients able to enroll beginning in 2028. Cigna expects at least 50% of eligible members to be enrolled in Signature models by the end of 2028. Kautzner said the company expects Pharmacy Benefit Services earnings growth of flat to 4% annually through 2030 as it manages a changing rebate environment and shifts toward a more predictable fee-based model. Efficiency initiative and capital plans. Dennison announced a $3 billion multiyear modernization and productivity initiative spanning 2026 through 2030. The effort will focus on workflow automation, workforce optimization and supplier, partner and vendor efficiency. She characterized the program as a savings initiative, with some savings reinvested in the business and some contributing to earnings. The company expects approximately $50 billion in cash flow from operations over the 2026-2030 period. Dennison said Cigna intends to prioritize business investment, maintain a dividend payout ratio of about 20%, continue share repurchases and pursue bolt-on acquisitions that are strategically aligned and financially accretive. The company said it has more than $6 billion remaining under its share-repurchase authorization. About Cigna Group (NYSE:CI). The Cigna Group NYSE: CI is a global health company that provides health care and related services to individuals, employers, government organizations and health plans. Its operations are primarily organized through Cigna Healthcare and Evernorth Health Services, which together address health coverage, pharmacy services, care delivery and benefit management. Cigna Healthcare offers medical, dental, behavioral health, disability and other benefits, with a focus on employer-sponsored and individual health plans in the United States as well as international health services. This instant news alert was generated by narrative science technology and financial data from MarketBeat in order to provide readers with the fastest reporting and unbiased coverage. Please send any questions or comments about this story to [email protected]. 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Virgin Media O2 deploys AI voice agent to handle support calls. Virgin Media O2 has launched an AI-driven voice agent to assist customers with selected broadband fault queries, partnering with enterprise conversational AI platform Sierra. The telco is rolling out the technology gradually, initially targeting a subset of routine broadband fault calls that comprise a small share of its overall contact volumes. The tool is designed to triage and resolve common, transactional issues automatically, allowing human frontline advisors to dedicate more time to complex, escalated, or emotionally sensitive queries. Customers interacting with the system retain the option to transfer directly to a human support agent. Virgin Media O2 confirmed that calls will be monitored internally to evaluate system performance and iterate based on customer feedback. The launch complements the operator's broader customer contact strategy. In recent months, the company established a dedicated UK-based team of more than 500 agents tasked with managing complex cases, such as vulnerable customer support and bereavement. In parallel, the brand partnered with the Institute of Customer Service to deliver accredited frontline training and introduced Lumi AI, an in-house agent-assist tool that delivers real-time conversational prompts to human representatives. According to data from regulatory body Ofcom, the provider has seen sustained reductions in consumer complaints over the preceding 18 months alongside an uptick in 24-hour resolution rates. Commenting on the deployment, Alan Stott, Chief Operating Officer at Virgin Media O2, said: "Customers want support that is quick, simple and effective, and our people want the right tools to help them deliver brilliant service. Launching this service is another step forward in our plan to use technology responsibly to improve the customer experience. "This is about supporting our people, not replacing them. By using AI to help with routine journeys, we can give customers faster support where it makes sense, while freeing up our advisors to focus on the complex, sensitive and human moments where their expertise and experience make the biggest difference. "We've made real progress improving customer service, from investing in specialist teams and accredited training to rolling out AI tools like Lumi that empower our advisors. But we know there is more to do, and we'll continue testing, learning and investing so we can deliver even better service for our customers." Bret Taylor, CEO and co-founder of Sierra, added: "The companies getting the most from AI start with a clear business goal and use AI to reach it - rather than approaching AI as a standalone project. Virgin Media O2 is doing exactly that, kicking off with a specific broadband use case where AI can help customers get support faster, then learning and expanding over time. We're so proud to partner with them to create effortless experiences for customers." Industry impact. Historically, voice automation in telecommunications has struggled with rigid, frustrating interactive voice response (IVR) menus that damaged customer satisfaction. By combining modern conversational voice AI with targeted triage - and clearly establishing a low-friction escalation path to specialized human agents - Virgin Media O2 is validating the emerging blueprint for hybrid contact centers. For the wider industry, this signals that enterprise AI adoption will increasingly prioritize deep, domain-specific execution over wholesale agent replacement, raising the bar for how Tier-1 service providers balance cost containment with brand-protective human escalation.