Innovaccer is building an AI Forward Deployed Engineering team focused on taking AI from concept to production inside customer environments. As an AI Forward Deployed Engineer, you will work directly with customers to design, build, and deploy AI agents and agentic workflows on Innovaccer’s Gravity platform.
Responsibilities:
- Design and implement AI agents that reason, plan, use tools, and execute actions
- Build agentic workflows combining LLMs, tools, memory, and orchestration layers
- Deploy AI solutions on the Gravity platform within aggressive timelines (weeks)
- Integrate agents with data pipelines, APIs, workflows, and enterprise systems
- Build AI-driven workflows using modern agentic frameworks such as: LangGraph, CrewAI, AutoGen, Semantic Kernel, LlamaIndex Agents, Haystack Agents
- Design workflow automation using orchestration platforms such as: n8n, Temporal, Prefect / Dagster
- Implement MCP (Model Context Protocol), function calling, and tool-using agents
- Apply agentic patterns such as ReAct, Plan-and-Execute, and multi-agent coordination
- Work directly with customer technical, data, and operational teams
- Understand real-world workflows, constraints, and success criteria
- Rapidly prototype, iterate, and harden solutions for live customer use
- Act as a trusted technical advisor during AI adoption and rollout
- Write production-grade code in Python and/or TypeScript
- Build and integrate APIs, services, and data pipelines
- Ensure reliability, observability, security, and performance of AI systems
- Design for failure modes, guardrails, retries, and human-in-the-loop workflows
- Convert customer-specific implementations into reusable agent patterns and workflows
- Document architectures, orchestration logic, and best practices
- Feed learnings back into Innovaccer’s AI and Gravity platform roadmap
Requirements:
- 2+ years of hands-on experience in software engineering, applied AI, or AI systems
- Strong, demonstrable experience building AI agents or agentic workflows (professional, academic, or open-source)
- Hands-on experience with modern agentic frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, LlamaIndex Agents, Haystack, or equivalent
- Experience with workflow orchestration or automation tools such as n8n, Temporal, Prefect, Dagster, or similar
- Strong understanding of: LLMs and prompt engineering, Tool-using agents, planning, memory, and execution loops, MCP (Model Context Protocol) and function/tool calling architectures
- Proficiency in Python and/or TypeScript
- Ability to ramp quickly on new platforms and ship working solutions fast
- Comfortable working directly with customers in ambiguous, fast-moving environments
- Strong communication, problem-solving, and ownership mindset
- Experience deploying AI solutions in production or regulated environments
- Familiarity with healthcare data, workflows, or enterprise data platforms
- Experience building APIs, microservices, or cloud-native systems (AWS, Azure, or GCP)
- Exposure to observability, tracing, evaluation, or monitoring of agentic systems
- Background in customer engineering, solutions engineering, consulting, or forward-deployed roles