Senior Forward Deployed Engineer

Elios, Inc.; Northern (KY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Elios, Inc. is seeking a seasoned AI/ML engineer to lead end-to-end GenAI delivery for healthcare and BFSI clients.

You will translate ambiguous client problems into production-worthy AI systems, prototype agentic workflows, and ship reusable frameworks beyond a single engagement. The role emphasizes hands-on coding, feature-level architectural ownership, and collaboration with client teams to ensure scalable, repeatable IP.

Qualifications

• 7+ years in data science or AI/ML engineering.
• Hands-on GenAI delivery experience.
• Experience with LangGraph, AutoGen, CrewAI, or OpenAI Agents SDK.
• Experience with Azure AI Foundry or AWS Bedrock AgentCore.

Responsibilities

• Lead technical delivery for a pod and stay hands-on in code.
• Prototype agentic workflows and ship reusable AI frameworks.
• Own feature-level architecture and implementation decisions within guardrails.
• Collaborate with client engineering teams to move builds into repeatable IP.
• Deliver AI MVPs and production-ready pipelines, patterns and docs.

Skills

GenAI delivery

Python

MLOps

Cloud platforms

System architecture

Tools

OpenAI Agents SDK

LangGraph

Azure AI Foundry

AWS Bedrock

Job description

Multi-agent orchestration LangGraph AutoGen OpenAI Agents SDK Azure AI Foundry Bedrock AgentCore Rapid prototyping Technical architecture Client-facing delivery Python Data science Machine learning LLM APIs RAG Docker CI/CD Git SQL REST APIs AWS Azure

Job Description

You'll lead technical delivery for a pod while staying hands-on in the code, building industry-specific GenAI solutions for healthcare and BFSI clients from the ground up. The core of the role is turning ambiguous client problems into production-ready AI systems, prototyping agentic workflows quickly, and shipping reusable frameworks that can carry beyond a single engagement.

You'll own feature-level architecture and implementation decisions within broader technical guardrails, partner closely with client engineering teams, and help move successful builds into repeatable internal IP. The work spans production AI and ML pipelines, multi-agent systems, retrieval-driven applications, and cloud-native deployment patterns.

Most of your time will be spent engineering, with meaningful time in technical research and architecture. Success here means you can translate client goals into clear engineering plans, co-develop with stakeholders in real time, and deliver AI MVPs that prove feasibility and hold up in production.

We're looking for someone with 7+ years in data science or AI/ML engineering and recent hands-on GenAI delivery experience. Strong candidates have built with frameworks such as LangGraph, AutoGen, CrewAI, or OpenAI Agents SDK, and have worked with agent platforms such as Azure AI Foundry or AWS Bedrock AgentCore. Experience in healthcare or financial services is helpful, especially if you've helped turn client-specific solutions into reusable frameworks or supported early solution scoping.