Senior AI Engineer, Agentic Platform

Remote

San Francisco (CA)

A distancia

USD 180.000 - 260.000

Jornada completa

Hace 12 días

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

Supera los filtros ATS

Ventajas ofrecidas por este puesto de trabajo

Company pension with employer match
Generous holiday allowance
Learning resources

Descripción de la vacante

We are looking for a product-minded AI engineer to turn customer needs into reliable agents. You will own the end-to-end delivery from requirements to deployment, building agents and tools on AWS Bedrock and shaping the user experience that customers trust.

You'll focus on production quality, coverage, and performance, with ownership of running, measuring, and iterating on real customer impact at scale.

Formación

  • 5+ years building production software or data-intensive systems for real customers.
  • Strong Python skills, including at least one LLM or agent feature shipped to production users.
  • Hands-on AWS experience, ideally Amazon Bedrock and Bedrock AgentCore.
  • Orchestration, tool and function design, context assembly, and multi-step workflows.
  • You've built retrieval over real business data with SQL and metrics fluency.
  • You've owned an eval loop for a generative system with labeled sets and regression gates.
  • You have opinions on AI agent behavior and decision-making.
  • You quantify adoption and task success, then share results with non-technical stakeholders.
  • You invest in harnesses that speed future tasks and ensure reliability.

Responsabilidades

  • Own the customer outcome by ensuring the agent meets real needs.
  • Build production agents and the tools they call on Bedrock, with MCP integration.
  • Turn serving layers into endpoints and usable tooling for agents.
  • Shape the experience: speed, confidence, explanations and next steps.
  • Collaborate across technical and non-technical teams to ship reliable solutions.

Conocimientos

Production software
Python
LLM/Agent feature
AWS Bedrock
Agent engineering
Retrieval grounding
SQL metrics
Eval loop
Product sense AI
Measurement narrative
Communication skills

Herramientas

Amazon Bedrock
Bedrock AgentCore
Agent runtimes

Descripción del empleo

We are looking for a product-minded AI engineer to turn what our customers are trying to decide into agents they actually rely on. AskWaive, our in-product assistant, is already live; the work now is quality, coverage, and an experience that wows.

This is not a role for a prompt author or a demo builder. We want an owner: someone who takes a customer need—already expressed through our serving layers and semantic layer—and turns it into an endpoint, a tool, and an experience that makes the customer measurably better at their job. Agent engineering, deployment, and testing are all part of delivery, not a handoff.

Our core data platform is owned by the team that built it. You'll build on top of it—and where data or infrastructure is holding an agent back, you'll have the standing to propose the change and drive it.

What You'll Do
  • Own the Outcome: Start from the customer, and stay with it until the agent is answering their needs better.

  • Build Agents and Tools: Build production agents and the tools they call—retrieval, multi-step workflows, action-taking—on Amazon Bedrock, with Bedrock AgentCore as our runtime and tools exposed over MCP (Model Context Protocol).

  • Turn Serving Layers Into Capability: Our semantic layer and service APIs are where customer needs are already expressed. Your job is turning them into endpoints and tools an agent can wield well—and knowing which metrics and entities it should reach at all.

  • Shape the Experience, Not Just the Endpoint: How an answer arrives—its speed, its confidence, its explanation, the next step it offers is the product. A technically correct response a customer ignores is a failure.

Who You Are
  • The Owner: You measure your work by whether customers made better decisions with the agent's help, not by whether it shipped.

  • The Agent Builder: You've taken an agent past the demo. You know the hard part is everything after it works once—coverage, grounding, cost, and the failure modes you only see at scale. You fix problems without waiting for a ticket.

  • The Experience Obsessive: You care how an answer lands, not just whether it was right. Trustworthy, fast, and legible beats clever.

What You'll Bring
  • Experience: 5+ years building production software or data-intensive systems used by real customers, with strong Python skills—including at least one LLM or agent feature you shipped to production users.

  • AWS & Agent Stack: Hands-on AWS experience, ideally Amazon Bedrock and Bedrock AgentCore. Equivalent agent runtimes transfer, but we build on AWS and you'll be productive faster if you have prior exposure.

  • Agent Engineering: Orchestration, tool and function design, context assembly, and multi-step workflows—you've made the design calls, not just the prompt calls.

  • Retrieval & Domain Grounding: You've built retrieval over real business data, you can explain how context gets selected and why an answer was wrong, and you have enough SQL and metric fluency to catch an agent answering with the wrong number.

  • Evaluation & Iteration: You've built or owned an eval loop for a generative system—labelled sets, regression gates, and a number you could defend when someone asked whether it got better.

  • Product Sense for AI: You have opinions about how an agent should behave—when to answer, when to ask, when to refuse, how to show its work—and you've shipped those opinions, not just argued them.

  • Measurement & Narrative: You've quantified what an agent actually delivered for users—adoption, task success, decision quality—and presented it to people who were never going to read your traces.

  • Working With Agents: You've used coding agents on real production work, you can tell correct output from merely plausible output, and you invest in the harnesses that make the next task faster.

  • Communication & Collaboration: Excellent communication and collaboration skills, with a track record of working across technical and non-technical teams.

Bonus Points For:
  • LLM observability tooling (Langfuse, LangSmith, or Arize).

  • Semantic layer or metrics-layer design (Ossie, dbt).

  • Field-service, logistics, or other operational SaaS domains.

  • Prior experience as a senior or lead engineer responsible for guiding technical direction.

Location: Remote (UK-based) with occasional collaborative team meetups.

Right to Work: Applicants must currently have the legal right to work in the UK. We are unable to provide visa sponsorship for this position at this time.

WHAT YOU SHOULD KNOW ABOUT US
  • Laid back but focused: We offer a flexible, collaborative work environment and a passion for developing innovative, best-in-class solutions that directly contribute to the success of our customers.

  • Impact-driven: We care deeply and deliver services and solutions that make a real difference in the lives of our clients and their businesses.

  • Trust & Inclusion: We openly accept others as they are and build strong partnerships based on trust and mutual respect.

RELAX, WE'VE GOT YOU COVERED
  • Competitive company pension scheme with employer match.

  • Generous holiday allowance / flexible time off plus UK bank holidays.

  • Enhanced maternity, paternity, and parental leave policies.

  • Ongoing learning resources.

  • Comprehensive Employee Assistance Programme (EAP) providing free 24/7 mental health, legal, and financial guidance.

EQUAL OPPORTUNITY

WorkWave is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees in accordance with the Equality Act 2010. Don't meet every single requirement? Studies show that women and underrepresented groups are less likely to apply for jobs unless they meet every qualification. If you feel you could make a great impact in this role, we encourage you to apply anyway!

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