Deployed Engineer, Professional Services

Langchain
Atlanta +9 more
RemoteCareer-pivot friendly

Who this role is best for

Experienced AI engineers with production agent expertise and strong client communication will find this remote, collaborative role with enterprise customers.

Best fit for

  • Candidates with 4+ years of Python experience and a track record of building production agent systems.
    — “4+ years of software engineering experience with deep expertise in Python
  • Individuals who can transition between advisory and embedded delivery roles with enterprise clients.
    — “Comfortable operating across the full spectrum from advisory to embedded delivery
  • Professionals with strong evaluation methodology skills for non-deterministic AI systems.
    — “Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems

Things to consider

  • This role demands long-term engagement and adaptability to different enterprise environments.
    — “Serve as a deployed engineer inside the customer's team for extended engagements
  • Compensation may vary significantly based on location and role level.
    — “Actual compensation and offerings will vary based on role, level, and location

How to stand out

  • Highlight experience with multi-agent patterns and state management in your resume and interviews.
    — “Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management
  • Emphasize your ability to translate vague enterprise workflows into concrete software specs.
    — “You'll translate vague enterprise workflows into concrete software specs
  • Showcase your hands-on experience with the full Agent Development Lifecycle (ADLC).
    — “Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Company

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

What success looks like

  • advising on agent architecture
  • building production-ready AI agents
Typical background
software engineeringAI systems

Skills & requirements

Required

Agent Architecture DesignEvaluation StrategyProduction GuidanceCo-buildingEmbedded DeliveryAI Systems

Preferred

Dataset CurationPost-training Techniques

Stack & domain

Software EngineeringPythonTypeScriptJavaScriptAI SystemsProduction Agent SystemsAgent Architecture DesignEvaluation Strategy ReviewBest-practice Production GuidanceLangchainLanggraphDeep AgentsMulti-agent PatternsState ManagementEvaluation MethodologiesPost-training TechniquesSupervised Fine-tuningHarness EngineeringTrace MiningModel SelectionClient-facing CommunicationArchitectural Decision ArticulationTechnical Stakeholder CommunicationTeam CollaborationProblem-solvingContinuous ImprovementThought LeadershipContent CreationRecruiting IndustryTalent Tech Space

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

Remote

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)

Similar roles