Deployed Engineer, Professional Services (NYC)

Langchain

New York, NY

Hybrid

Who this role is best for

Strong fit for engineers with hands-on experience in AI agent systems who can transition between advisory and embedded work arrangements.

Best fit for

Engineers with 2+ years of experience building production AI agents and a track record of translating enterprise workflows into technical solutions
— “2+ years of hands-on experience building and shipping production agent systems”
Candidates comfortable with client-facing communication and explaining complex architectural decisions to technical stakeholders
— “Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders”
Individuals with experience in LangChain/LangGraph/Deep Agents frameworks and evaluation of non-deterministic AI systems
— “Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management”

Things to consider

The role demands a high level of adaptability to work across advisory and embedded delivery models
— “Comfortable operating across the full spectrum from advisory to embedded delivery”

How to stand out

Highlight specific examples of agent architecture design and evaluation pipeline development in your resume and interview responses
— “Agent architecture design, evaluation strategy review, and best-practice production guidance”
Emphasize your experience with Python and frameworks like LangChain or LangGraph in your application materials
— “4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus.”
Showcase your ability to work directly with enterprise engineering teams and deliver production-ready systems
— “Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly”

Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Individual

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

advises on agent architecture design
builds evaluation pipeline
serves as embedded engineer
builds reliable, production agents

Typical background

4+ years software engineering experience2+ years building and shipping production agent systemsdeep expertise in Python

Skills & requirements

Required

Agent Architecture DesignEvaluation Strategy ReviewBest-practice Production GuidanceCo-building Evaluation PipelineEmbedded DeliveryAgent EngineeringADLC End-to-endPythonLangchain/langgraph/deep AgentsEvaluation Methodologies For Non-deterministic AI Systems

Preferred

Dataset CurationPost-training Techniques

Stack & domain

PythonTypescript/javascriptAI SystemsLangchainLanggraphDeep AgentsEvaluation MethodologiesDataset CurationPost-training TechniquesCommunicationProblem-solvingTeamworkLeadershipCritical ThinkingAI EngineeringAgent DevelopmentProduction Deployment

About the role

Original posting from Langchain via Ashby

ABOUT US
At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.
With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.
Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.
ABOUT THE ROLE
We're looking for a Deployed Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them.
KEY RESPONSIBILITIES
Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance.
Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements.
Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly.
Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment.
Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology.
REQUIREMENTS
4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus.
2+ years of hands-on experience building and shipping production agent systems.
Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs).
Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory).
Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems.
Comfortable operating across the full spectrum from advisory to embedded delivery.
NICE TO HAVE
Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers, or TRL.
Experience with trace mining to drive continuous improvement loops
LOCATION
New York, New York
COMPENSATION
$150,000-$215,000 base + equity
Compensation Philosophy:
We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
BENEFITS
Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Source: Langchain careers (Ashby)