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Edra

<div>
 
 About Edra
 
 
 
 Edra is solving one of the hardest problems in enterprise AI: AI models are generic but company processes are specific. We build AI agents that learn how processes actually run, and then run their operations.
 
 
 We're a Series A startup, backed by Sequoia and other leading VC firms, led by Co-Founders who created and led Forward Deployed AI Engineering at Palantir, and we're growing our team in New York and London. We're a deeply technical team of engineers, AI researchers, and strategists with a high bar for talent and a shared belief that exceptional people are the foundation of everything great we'll build.
 
 
 
 The Role
 
 
 
 We're building a learning system that teaches AI agents how enterprises actually work. Our system ingests knowledge bases, conversations, tickets, and system logs, then produces written instructions that agents can execute&ndash;with confidence scoring to know when to automate and when to seek human input.
 
 
 We're looking for AI Engineers who have built complex, production LLM-based systems. Whether you've scaled LLM workflows handling millions of requests, built multi-agent systems in production, or designed evaluation frameworks for enterprise deployments, we want people who bring intensity and self-direction to their craft.
 
 
 You&rsquo;ll spend most of your time advancing our core learning library and building the harness that powers our platform&rsquo;s agents across all customers. The work spans continuous learning systems, agentic features, human-in-the-loop feedback loops, and agent orchestration.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Build and extend our core context-learning library, turning customer-informed problems into reusable platform capabilities.
 </li>
 <li>
 Design and implement LLM-powered systems and agentic workflows from concept to production
 </li>
 <li>
 Build agentic features for knowledge management&ndash;think agents that can edit, update, and maintain large knowledge bases autonomously
 </li>
 <li>
 Build reliability and confidence systems&ndash;evaluation frameworks, confidence scoring, and logic for when to automate vs. when to escalate to a human
 </li>
 <li>
 Architect async, scalable systems that handle complex AI orchestration
 </li>
 <li>
 Contribute to the direction of our AI strategy and product capabilities
 
 
 </li>
 </ul>
 
 What We&rsquo;re Looking For
 
 
 
 <ul>
 <li>
 You've built complex, production LLM-based systems with real depth&ndash;something with multiple layers of engineering decisions you can walk through in detail
 </li>
 <li>
 You've shipped something meaningful to production and can explain how it evolved
 </li>
 <li>
 You're excited by open-ended problems where the solution might not exist yet
 </li>
 <li>
 You have experience with (or strong interest in) how systems learn and improve over time: human-in-the-loop feedback, prompt optimization and context engineering
 </li>
 <li>
 You have experience building agents and autonomous systems
 </li>
 <li>
 You can navigate between research papers and production code with equal comfort
 </li>
 <li>
 You're a strong communicator who can clearly explain your work to teammates and customers
 </li>
 <li>
 You have 3+ years of professional experience
 
 
 </li>
 </ul>
 Don&rsquo;t meet all of the above traits? We&rsquo;d still love to hear from you. We&rsquo;re looking for exceptional people with unique skills and interests, and we know that great people have different backgrounds and skillsets.
 
 
 
 Learn More About Edra
 
 
 
 <ul>
 <li>
 Watch our Series A announcement video
 </li>
 <li>
 Read our blog post from our launch
 </li>
 <li>
 Learn more about what we're building
 
 
 </li>
 </ul>
 
 Compensation &amp; Benefits
 
 
 
 Edra offers generous compensation and benefits in both New York &amp; London:
 
 
 <ul>
 <li>
 Competitive base salary &amp; meaningful equity
 </li>
 <li>
 Top tier health, dental, &amp; vision plans:
 </li>
 <ul>
 <li>
 Top plans with 100% premium coverage in the US (and a One Medical membership)
 </li>
 <li>
 Private medical &amp; dental coverage in the UK
 </li>
 </ul>
 <li>
 Flexible paid time off
 </li>
 <li>
 Lunch provided in office most days, snacks &amp; drinks too
 </li>
 <li>
 A stipend to set up your workspace
 
 </li>
 </ul>
 
 A Few Details
 
 
 
 We work together in person five days a week from our offices in the West Village (New York) and Holborn (London).
 
 
 Edra is an equal opportunity employer and we encourage applications from individuals of all backgrounds. Edra does not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, marital status, sexual orientation, gender identity, veteran status, or any other legally protected characteristic.
 
 
 Compensation Range: $200K - $300K
 
 
</div>

AI Engineer (New York)

Ameriprise Financial

<div>About Our Company 
We&rsquo;re a diversified financial services leader with more than $1.5 trillion in assets under management, administration and advisement as of year-end 2024. Our team of 22,000 people across 19 countries, serves more than 3.5 million individual, small business and institutional clients. We are a longstanding leader in financial planning and advice, a global asset manager and an insurer. Our unwavering focus on our clients and strong financial foundation connects each of our unique businesses &ndash; Ameriprise Financial, Columbia Threadneedle Investments and RiverSource Insurance and Annuities. Here, we foster meaningful careers, invest in the future, and make a difference for clients, institutions and communities around the world.
Job Description
The VP-Forward Deployed Engineer operates at the intersection of investment strategy, quantitative analysis and applied artificial intelligence. The position is responsible for partnering closely with portfolio management and investment research teams to identify opportunities, design solutions, and develop, prototype, and deploy LLM-enabled tools that enhance investment decision-making and research processes. Combines investment management knowledge with software engine capabilities to translate investment ideas and research needs into scalable technology solutions.
Key Responsibilities<ul><li>
Serve as a trusted advisor to investment leaders, translating investment strategies, research priorities, and business challenges into innovative AI-enabled solutions that improve investment outcomes and organizational efficiency.</li><li>
Drive the design and delivery of proof-of-concept and production-ready AI capabilities, leveraging advanced analytics, machine learning, and LLM technologies to accelerate investment insights and decision-making.</li><li>
Partner across Investments, Technology, Data, Risk, and Compliance functions to ensure solutions meet enterprise standards for security, governance, scalability, and regulatory compliance.</li><li>
Influence the AI and investment technology roadmap by identifying high-value opportunities, evaluating emerging capabilities, and promoting adoption of innovative solutions across the investment organization.</li><li>
Lead the transition of successful prototypes into sustainable enterprise capabilities, partnering with engineering and platform teams to scale solutions and realize long-term business value.</li></ul> 
Required Qualifications<ul><li>
10+ years of combined experience across investment management, quantitative research/strategy, and hands-on software or AI engineering, with demonstrated success taking investment problems from concept to working solution.</li><li>
Direct experience working alongside trading desks, portfolio managers, or investment researchers, with desk strategist, quant strat, or research technologist backgrounds strongly preferred.</li><li>
Hands-on experience building and shipping LLM enabled/integrated applications: RAG/embeddings, agentic workflows, prompt engineering, API integration.</li><li>
Strong Python development skills producing production-quality code.</li><li>
Expertise with cloud infrastructure and modern software practices (CI/CD, version control, API design).</li><li>
Fluency in at least one asset class (equities, fixed income, multi-asset, or macro) at a level where you can challenge and contribute to investment discussions, not just support them.</li><li>
Track record of delivering secure, auditable AI solutions in a regulated environment, partnering with risk and compliance.</li></ul> 
Preferred Qualifications<ul><li>
Direct experience supporting front-office investment teams (portfolio managers, analysts, researchers, traders).</li><li>
Familiarity with agent frameworks and orchestration tools (LangChain, LangGraph, LlamaIndex, MCP) and vector databases.</li><li>
Experience building internal copilots, research assistants, or document-intelligence tools.</li><li>
CFA, FRM, or equivalent investment credential.</li><li>
Track record of shipping AI or analytics solutions that produced measurable, real-world outcomes.</li></ul>
Visa Sponsorship 
Applicants must have a valid work authorization that does not now, or in the future, require visa sponsorship for employment in the United States (e.g., H-1B, F-1 CPT, F-1 OPT, TN).
In-Office Collaboration 
We are a client-centric, relationship-based business. Working together, in-person, is foundational to how we achieve results. By fostering a culture of face-to-face collaboration, idea sharing, productivity and personal connection, we deliver for our stakeholders &mdash; clients, advisors, employees and shareholders. Our employees work in the office at least four (4) days per week, with flexibility to work from home one (1) day per week. Some roles may require additional in-office time or different in-office expectations, and specific requirements will be discussed during the hiring process. 
Base Pay Salary
The estimated base salary for this role is $242,100 - $332,900 / year. We have a pay-forperformance compensation philosophy. Your initial total compensation may vary based on job-related knowledge, skills, experience, and geographical work location. In addition, most of our roles are eligible for variable pay in the form of bonus, commissions, and/or long-term incentives depending on the role. We also have a competitive and comprehensive benefits program that supports all aspects of your health and well-being, including but not limited to vacation time, sick time, 401(k), and health, dental and life insurances.<div><div><div><div><div><div><div>
Full-Time/Part-Time</div></div></div></div></div></div></div>
Full time<div><div><div><div><div><div><div>
Exempt/Non-Exempt</div></div></div></div></div></div></div>
Exempt<div><div><div><div><div><div><div>
Job Family Group</div></div></div></div></div></div></div>
Data<div><div><div><div><div><div><div>
Line of Business
</div></div></div></div></div></div></div>TECH Technology
Ameriprise Financial is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, ancestry, age, physical or mental disability, medical condition, pregnancy, military status, veteran status, genetic information, citizenship, disability status, marital status, family status or any other basis prohibited by law.
We are committed to fostering an inclusive and accessible recruitment process for individuals with disabilities. If you require a reasonable accommodation to participate in the application or interview process, speak to your recruiter to discuss how we can support you.</div>

Vice President - Forward Deployed Engineer

Qureos

About the company: We build AI hiring agents. They deploy inside the enterprise systems a company already runs, or on the Qureos platform itself for teams who would rather have the whole hiring stack in one place. Either way the agents do the work recruiting teams have always done by hand, from sourcing and screening to interviewing and shortlisting, with speed and consistency no agency or traditional ATS can match. We are a Seed-stage startup backed by Prosus Ventures and COTU Ventures, having raised $5M to accelerate the future of AI-powered hiring. Trusted by more than 1,000 enterprise and public sector organizations, we're scaling rapidly as we build the next generation of AI hiring agents. Operating in a market where every unfilled role and every slow hiring loop costs real money, we are building the future of AI-powered hiring. Our agents let companies run high-volume hiring end to end without ripping out the systems their teams already live in. About the Role As a Forward Deployed Engineer, you will sit at the intersection of engineering, AI, and customer impact. You will work directly with customers to understand how they hire, find the parts of that process worth handing to an agent, and then design, build, and deploy those agents either into the customer's existing enterprise stack or onto the Qureos platform, depending on how they want to run. <ul><li>You will partner closely with customers and Qureos's product and engineering teams to customise agent workflows, improve agent performance, and bring what you learn in live deployments back into the core platform.</li><li>This role is ideal for an engineer who enjoys building production systems, working inside someone else's environment, solving ambiguous problems, and shaping how AI actually gets used in hiring.</li></ul> What You'll Do <ul><li>Embed directly with customers to understand their hiring processes, the systems those processes run on, and where an agent can take over.</li><li>Design, build, and deploy AI hiring agents that source, screen, interview, and move candidates through the funnel.</li><li>Ship those agents into the customer's existing enterprise environment, or onto the Qureos platform for customers who want the all-in-one setup.</li><li>Develop and maintain the infrastructure behind the agents, including APIs, integrations with enterprise ATS and HRIS systems, monitoring, and feedback loops.</li><li>Translate customer requirements into scalable technical solutions and production-ready deployments.</li><li>Collaborate with product and engineering teams to influence roadmap decisions based on what you see in the field.</li><li>Identify patterns across customer deployments and turn one-off integration work into something the platform supports natively.</li><li>Work across engineering, product, and customer teams to ensure successful adoption and long-term impact.</li><li>Operate independently in fast-moving environments where ownership and initiative are highly valued.</li></ul> What You'll Bring <ul><li>3+ years of software engineering experience, preferably with backend, infrastructure, or systems-focused development.</li><li>Strong programming experience in Python (experience with TypeScript/JavaScript is a plus).</li><li>Experience working with cloud platforms such as AWS, GCP, or Azure.</li><li>Ability to design and build reliable production systems, including inside environments you do not control.</li><li>Strong communication skills with the ability to work with both technical and non-technical stakeholders.</li><li>Experience working directly with customers, partners, or cross-functional teams is a plus.</li></ul> Bonus: experience with AI agents, large language models (LLMs), vector databases, prompt engineering, retrieval-augmented generation (RAG), voice agents, or integrating with enterprise ATS and HRIS platforms. Comfortable working in dynamic environments with changing priorities and high ownership. Why Join Us You'll be part of a team building a category-defining AI company in a market that has barely started to change. We move fast, we ship, and we work close to the customer. If you are excited about building AI agents that do real work, deploying them into the systems enterprises actually run, and shaping how hiring gets done, we'd love to hear from you.

Forward Deployed Engineer

Product Marketing Lead, Instagram Reels Monetization and Ads Experiences

Palo Alto Networks

<div><div>Santa Clara, California, United States of America
 
New York, New York, United States of America
 
Plano, Texas, United States of America Product Engineering Ref ID: JR-020960</div><div> 
</div><div>Our Mission
At Palo Alto Networks&reg;, we&rsquo;re united by a shared mission&mdash;to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you&rsquo;re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you&rsquo;re in the right place.
Who We Are
In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us!
We believe collaboration thrives in person. That&rsquo;s why most of our teams work from the office full time, with flexibility when it&rsquo;s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes.
Job Summary
As a Forward Deployed Engineer (FDE) for AI Gateway, you are a hands-on developer and systems architect who embeds with customer engineering teams. You write production code, design low-latency topologies, and build custom plugins to ship secure enterprise AI workloads to production. You bridge the gap between customer production environments and core engineering&mdash;extending the platform edge while directly contributing code back to the core AI Gateway engine.
Key Responsibilities
<ul><li>Write production-grade code (Python, Go, TypeScript) to integrate AI Gateway with microservices, API meshes, and multi-cloud architectures.
</li><li>Build custom middleware/plugins for identity-aware policies, prompt security, dynamic routing, and telemetry pipelines.
</li><li>Develop automated deployment modules (Terraform, Helm, Kubernetes) and SDK wrappers.
</li><li>Optimize high-throughput, low-latency traffic paths (streaming payloads, caching, load balancing).
</li><li>Lead Architectural Design Reviews (ADRs) with customer Principal Engineers and CISOs for zero-trust deployments.
</li></ul>Qualifications
Required Qualifications
<ul><li>7+ years writing production code (Python, Go, TypeScript/C++), with deep experience in APIs (gRPC, REST, WebSockets) and API gateways (Envoy, Kong).
</li><li>Hands-on experience with LLM orchestration, prompt security, token optimization, model routing, and vector databases/RAG architectures.
</li><li>Proficiency in Kubernetes, Docker, Terraform, AWS/GCP/Azure, OIDC/OAuth2, and zero-trust networking.
</li></ul>Preferred Qualifications
<ul><li>A hands-on builder who loves pair-programming with customer devs and digging into raw code/traces to solve live outages.
</li><li>Experience thinking like an engineer first and a consultant second.
</li><li>Proven ability to own problems end-to-end.
</li><li>Ability to whiteboard enterprise architecture, debug an API integration, review code, and influence the product roadmap.
</li></ul>Compensation Disclosure
The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus.
$147,000.00 - $237,500.00/yr
Our Commitment
We&rsquo;re trailblazers that dream big, take risks, and challenge cybersecurity&rsquo;s status quo. It&rsquo;s simple: we can&rsquo;t accomplish our mission without diverse teams innovating, together.
We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at accommodations@paloaltonetworks.com.
Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics.
All your information will be kept confidential according to EEO guidelines.
Is role eligible for Immigration Sponsorship?: Yes</div></div>

Senior Forward Deployed Engineer (Customer Engineering)

Tessera Labs

<div>
 
 About Tessera Labs
 
 
 
 Tessera Labs is a new category of enterprise software: an AI platform that changes how the world's largest companies run.
 
 
 Every large enterprise carries the same weight &mdash; decades of accumulated process, data, and code that no longer match the business it has become. Changing any of it is a program measured in years and hundreds of millions of dollars, staffed by armies of consultants, and it fails more often than anyone admits. Most companies have quietly accepted this as the cost of being large.
 
 
 We don't. Tessera is a transformation engine: a governed, multi-agent platform that understands an enterprise's process, data, and code as one connected system and changes it in weeks rather than years. We're vendor-agnostic by design &mdash; SAP, Salesforce, Workday, Oracle, Snowflake, MuleSoft &mdash; and tied to none of them.
 
 
 Two things make this hard, and they're the reason the job is interesting. Governance: every action is logged, traceable, and reversible, because our customers are regulated and these are the systems that close their books. And generality: the platform has to work on landscapes it has never seen, at companies whose complexity is genuinely unique to them.
 
 
 
 We sell a product, not a service.
 
 Our people are here to make the product successful, not the other way around. If you've watched enterprise AI companies quietly become consultancies, that distinction is the one to press us on.
 
 
 We raised a $60M Series A led by Andreessen Horowitz, with Foundation Capital, Myriad Venture Partners, and Osage University Partners participating.
 
 
 
 About The Role
 
 
 
 Turning platform capability into outcomes a Fortune 500 will bet on has two halves &mdash; the systems that surround the model, and the model itself. This role owns the first.
 
 
 You will own agents end to end: the harness they run in, the tools they call, the context they see, the guardrails around them, and the evals that tell us whether any of it is improving. Most of the difficulty is not model access. It's an agent reasoning across a landscape with nineteen years of undocumented decisions embedded in it, where one call silently returns a stale schema forty steps into a plan &mdash; and the work of making that failure legible, reproducible, and then impossible.
 
 
 This is not a prototyping role. Everything you build gets pointed at systems a company's quarter close depends on.
 
 
 
 If the model itself interests you more than the systems around it, look at Research Engineer &mdash; same team, other half of the problem.
 
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Design and ship the production agents that do transformation work: understanding a landscape, planning a change, executing it across process, data, and code, and proving it was correct.
 </li>
 <li>
 Build the tool layer &mdash; typed, permissioned, well-documented interfaces that let agents read and act across enterprise systems without ever exceeding what a human approver authorized.
 </li>
 <li>
 Improve agent performance through prompting, context construction, tool-use strategy, and decision logic &mdash; and know which of those a given failure calls for.
 </li>
 <li>
 Build the retrieval layer over enterprise artifacts and metadata: chunking and indexing strategies for content that doesn't resemble prose, hybrid search, reranking, grounding, and the evaluation that tells you whether any of it helped.
 </li>
 <li>
 Manage context deliberately. Enterprise artifacts are enormous and a forty-step run accumulates history fast; deciding what the model sees, what gets compressed, and what gets dropped is a first-class engineering problem here, not a prompt detail.
 </li>
 <li>
 Use classical ML where it's the right tool. Plenty of the work inside an agent pipeline &mdash; routing, ranking, classification, anomaly detection, confidence estimation &mdash; is better served by a small supervised model than by another LLM call, and knowing the difference is part of the job.
 </li>
 <li>
 Build the eval and monitoring layer: task sets drawn from real customer landscapes, regression coverage on every deploy, and alerting that catches a changed schema, a revoked authorization, or a new model version before the customer does.
 </li>
 <li>
 Instrument every run so each model call, tool invocation, decision, and human approval can be reconstructed afterward. This is what "passes audit" means in practice, and it's a product requirement rather than a nice-to-have.
 </li>
 <li>
 Diagnose production failures from execution traces down to root cause, then close the gap in the system rather than in a single prompt.
 </li>
 <li>
 Design the guardrails, approval gates, and rollback paths that make an agent safe to point at a live enterprise landscape.
 </li>
 <li>
 Build capability that generalizes. Anything that only works for one customer is a bug in the product, not a feature of the engagement.
 
 
 </li>
 </ul>
 
 Representative projects
 
 
 
 <ul>
 <li>
 Shipping the agent that lets a customer retire a third of their custom estate in a quarter &mdash; and the review surface that makes a human comfortable approving each call in minutes rather than days.
 </li>
 <li>
 Designing the approval and write semantics for agents operating in a live landscape, so nothing reaches production without a traceable human decision and no partial failure leaves systems inconsistent.
 </li>
 <li>
 Building the reconciliation agent that makes two merged companies' data agree, plus the eval set that tells us when it's confident and when it's guessing.
 </li>
 <li>
 Standing up the replay-evaluation pipeline that scores a candidate agent version against a month of recorded runs &mdash; real system responses, mocked writes &mdash; so a regression is caught before anything is touched in a customer environment.
 </li>
 <li>
 Taking a pattern that worked at one customer and turning it into a platform primitive that works at the next four without a human rewriting it.
 
 
 </li>
 </ul>
 
 You may be a good fit if you
 
 
 
 <ul>
 <li>
 Have 3+ years building and operating production software, with meaningful recent time on LLM-powered systems.
 </li>
 <li>
 Have shipped agentic systems that real users depend on, and have owned the incident when they broke.
 </li>
 <li>
 Are fluent in the current agent toolkit &mdash; tool calling, orchestration, context engineering, RAG, evals, tracing &mdash; and can say where each one stops working.
 </li>
 <li>
 Have built retrieval systems against messy real-world corpora, and have measured them rather than assumed them.
 </li>
 <li>
 Have real traditional ML in your background &mdash; supervised learning, feature engineering, model evaluation &mdash; and reach for it when it beats a prompt.
 </li>
 <li>
 Treat evaluation as engineering rather than a report you generate at the end.
 </li>
 <li>
 Think in systems and customer outcomes, not model metrics.
 </li>
 <li>
 Are comfortable with non-determinism and have opinions about building reliably on top of it.
 </li>
 <li>
 Write strong Python and are comfortable in TypeScript.
 </li>
 <li>
 Ship fast, and verify before you claim it works.
 </li>
 <li>
 Find large, ugly, undocumented enterprise systems interesting rather than beneath you. That instinct is most of the job, and it's rarer than it should be.
 
 
 </li>
 </ul>
 
 Strong candidates may also have
 
 
 
 <ul>
 <li>
 Hands-on experience with enterprise platforms, their APIs, and their extension models &mdash; SAP, Salesforce, Workday, Oracle, Snowflake, MuleSoft, ServiceNow.
 </li>
 <li>
 Experience with knowledge graphs, ontologies, or semantic models over messy real-world systems.
 </li>
 <li>
 Experience with code analysis, program transformation, or automated refactoring at scale.
 </li>
 <li>
 Experience with MCP, sub-agents, or agent skill/plugin architectures.
 </li>
 <li>
 A background in distributed systems or workflow engines, where partial failure is the default case.
 </li>
 <li>
 Experience at an early-stage startup or as a founder, where scope was whatever needed doing that week.
 </li>
 <li>
 Familiarity with enterprise security and compliance realities: SSO, RBAC, segregation of duties, PII handling, SOC 2, data residency.
 
 
 </li>
 </ul>
 
 Join the Future of AI at Tessera Labs
 
 
 
 We're looking for someone who enjoys building reliable, scalable systems that help teams move faster. If you take pride in cutting-edge AI, value clear ownership, and want to have a meaningful impact in a fast-moving environment, you&rsquo;ll fit right in.
 
 
 No third party may recruit, solicit candidates, publish job opportunities, use Tessera Labs&rsquo; name or branding, or represent that they are acting on behalf of Tessera Labs without prior written authorization. Any such activity conducted without explicit written consent is strictly prohibited.
 
 
 Compensation Range: $200K - $250K
 
 
</div>

AI Engineer

SERVAL

<div><h1 class="jobSectionHeader">Who We Are</h1>
Serval is an AI-native automation platform transforming how enterprises operate. We build intelligent agents that understand real-world workflows and execute them end-to-end &mdash; replacing manual processes and rigid legacy systems with adaptive, learning software. Founded in early 2024, Serval is already trusted by companies like Fox, Notion, Perplexity, Vercel, and Brex to automate high-volume, high-friction operational work across their organizations. 
 
At the core of Serval is an agentic AI platform that turns natural language into production-grade workflows. Our agents don&rsquo;t just respond to requests &mdash; they reason, take action across systems, and continuously improve with usage. What began with operational use cases has quickly evolved into a horizontal AI automation layer used across IT, HR, Finance, Security, Legal, and Engineering. 
 
Our mission is to eliminate repetitive, manual work across the enterprise and give teams leverage through intelligent automation. Long term, we&rsquo;re building the universal AI operations layer &mdash; a system of agents that sits across business functions and runs the workflows that keep modern companies moving. 
 
We&rsquo;re backed by leading investors including Sequoia Capital, Redpoint Ventures, Meritech, First Round, General Catalyst, Elad Gil, and others.
<h1 class="jobSectionHeader">About the team</h1>
The Agent Deployment team is a customer-facing technical team, central to how Serval turns product capability into real business outcomes. The org is a family of roles: Deployment Strategists are the primary technical relationship and AI advisor for each customer, partnering with Deployed Software Engineers to build enterprise-grade features and products. Deployment Success Managers own each customer's long-term success, building the systems and motions that scale adoption, expansion, and renewal well past go-live.<h1 class="jobSectionHeader"> 
Role Overview</h1>
As a Deployment Strategist on Serval's Agent Deployment team, you&rsquo;ll be the primary technical relationship for Serval&rsquo;s customers: guiding their deployments, advising their AI strategy, and owning their outcomes. You&rsquo;ll work deeply within Serval&rsquo;s existing product surface area: building novel workflows, configuring integrations, and shipping bug fixes and product changes yourself.
This role is for someone who thrives on execution velocity, moving quickly across multiple engagements at once. You&rsquo;re at home in ambiguity and bring a strong blend of technical depth, product sense, and customer obsession. And because you sit closest to how customers actually use Serval, you'll directly shape our product roadmap: the workflows and features you build in the field make their way into the core product.<h1 class="jobSectionHeader">
What You&rsquo;ll Do</h1><ul><li>
Own customer engagements from pilot through production launch: design and deliver deployments that fit each customer's workflows and scale adoption of Serval.</li><li>
Build AI agents: design and build AI agents on Serval's platform that drive real value for customers.</li><li>
Advise AI strategy: embed with customers to guide and shape how they adopt and scale AI.</li><li>
Lead migrations: design and execute migration plans that minimize disruption and ensure seamless adoption of Serval's platform.</li><li>
Partner cross-functionally: work with Engineering, Sales, and Marketing to turn field learnings into repeatable processes and a sharper go-to-market.</li></ul><h1 class="jobSectionHeader">
What You&rsquo;ll Need</h1><ul><li>
Degree in Computer Science or a related field, or equivalent hands-on experience.</li><li>
5+ years in a relevant role (product, engineering, consulting, founder).</li><li>
Strong communication and relationship management skills, with the ability to translate complex technical concepts for both technical and non-technical stakeholders.</li><li>
Hands-on technical ability: reading and troubleshooting production code in customer-facing environments, analyzing code paths, database state, and API requests/responses with infra and browser dev tools.</li><li>
Working knowledge of APIs and REST, IAM, and SQL for data analysis.<div> 
</div></li></ul><h1 class="jobSectionHeader">
Nice to Have</h1><ul><li>
Experience in an early-stage startup environment.</li><li>
Experience writing production code.</li><li>
Background working with enterprise customers or complex technical sales cycles.</li><li>
Familiarity with IT, security, service management, or workflow automation.</li></ul><h2 class="jobSectionHeader">
What We Offer</h2><ul><li>
Impact: Be a key player in shaping the success of our product and company.</li><li>
Growth: Build a fundamentally new AI product offering with the support of our experienced team and investors. Grow rapidly with the company.</li><li>
Culture: Join a culture that values innovation, ownership, accountability, and fun.</li></ul>
Compensation Range: $150K - $280K</div>

Deployment Strategist

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