About the role
The Forward Deployed Engineer designs, builds, and deploys production-grade multi-agent systems within regulated enterprise environments.
This role is responsible for developing scalable AI applications, retrieval pipelines, orchestration frameworks, APIs, observability tooling, and production infrastructure while working closely with Architects, Delivery teams, and enterprise client stakeholders. The role requires strong hands-on engineering capability, production delivery experience, and a strong understanding of enterprise AI engineering practices. All engineers use AI tools effectively in their daily work. AI assistants and workflow automation tools are expected to improve engineering productivity, testing, debugging, documentation, and delivery execution.
What You Will Do
- Design and deliver production-grade multi-agent systems using orchestration frameworks such as LangGraph, LangChain, CrewAI, or equivalent technologies.
- Build and maintain end-to-end RAG pipelines including chunking strategies, embedding evaluation, retrieval optimization, reranking, and hallucination evaluation.
- Develop prompt frameworks, role instructions, escalation flows, and guardrail mechanisms for enterprise AI applications.
- Implement production-grade AI guardrails including PII redaction, input sanitization, output validation, adversarial testing, and security controls.
- Design and deploy AI systems within in-region and in-VPC enterprise environments using AWS services and regulated deployment architectures.
- Build and maintain FastAPI services, streaming APIs, authentication layers, React-based interfaces, and enterprise integrations.
- Deploy and manage workloads on ECS, EKS, SageMaker, Bedrock, API Gateway, and related AWS infrastructure services.
- Implement CI/CD pipelines, automated testing workflows, infrastructure automation, observability tooling, and production monitoring frameworks.
- Define and execute testing strategies including unit testing, integration testing, retrieval testing, adversarial testing, and evaluation frameworks.
- Contribute to architecture reviews, low-level designs, solution documentation, and technical proposal responses.
- Lead technical workstreams within engagements and support junior engineering team members through reviews, debugging, and technical guidance.
- Contribute reusable engineering assets including runbooks, prompt libraries, evaluation frameworks, deployment templates, and tooling accelerators.
What you’ll bring
Benefits and perks
Skills
Required
ragLLMMulti-Agent SystemsModel Context Protocol (MCP)Retrieval-Augmented Generation (RAG)Artificial IntelligenceAI Agents
Nice to have
PythonJavaSQLJavaScriptLinuxClient CommunicationProject Management