Forward Deployed Engineer

Multiple AI roles_FDE–Agentic AI/AI Prompt Engineer/AI Lead Engineering/AI Architect / FDE – Healthcare_New York, Bay Area, Dallas, or Chicago Work model: hybrid, with no fully remote option. Travel: approximately 25% when necessary. Office attendance: the exact weekly onsite schedule remains pending. JD1:Forward Deployed Engineer – Agentic AI This role combines senior client engagement with hands-on engineering, translating business challenges into working AI solutions and taking them from rapid proofs of value toward MVP and production delivery. 8+ years in full-stack engineering, solution architecture, or technical consulting, with significant client-facing delivery.
- Strong Python plus TypeScript, Java, or Go.
- Practical experience with LLMs, agent orchestration, tool calling, planning/execution loops, and memory patterns.
- RAG, embeddings, chunking, vector databases, and retrieval evaluation.
- APIs, data pipelines, enterprise integrations, and sound software architecture.
- Cloud-native engineering on AWS, Azure, or GCP, including containers, CI/CD, and observability.
- Prioritize engineers who personally build solutions, develop evaluation methods, and address security, access controls, human oversight, reliability, latency, and cost. Production GenAI experience and integrations with platforms such as ServiceNow, Salesforce, SAP, Microsoft, Databricks, or Snowflake are preferred. ---------
- JD2: AI Prompt Engineer / Agentic AI Engineer This is a hands-on engineering role focused on developing agents that reason, use tools, and execute enterprise workflows. Experience building LLM applications and agent workflows using Semantic Kernel, LangChain, LangGraph, AutoGen, CrewAI, or comparable frameworks.
- Python, TypeScript, or similar programming languages.
- Prompt optimization, agent planning, memory, context management, and multi-step execution.
- RAG, embeddings, vector databases, and knowledge grounding.
- Familiarity with Azure AI Foundry, Azure OpenAI, AWS Bedrock, Google Vertex AI, or comparable platforms.
- Agent evaluation, testing, deployment, monitoring, troubleshooting, security, and governance. Enterprise copilots, AI assistants, and healthcare or regulated-system integrations are preferred. The supplied JD does not specify a minimum number of years, so please assess demonstrated engineering depth rather than imposing the FDE or platform-engineering experience threshold. ----------
- JD3: AI Lead Engineering – Enterprise AI, Cloud & Platform Transformation This role combines AI engineering with enterprise platform design, cloud transformation, and production operations. 12+ years across AI, DevOps, cloud engineering, SRE, or platform engineering.
- 3+ years of hands-on AI-stack experience.
- 5+ years designing enterprise platforms.
- 3+ years implementing AIOps or observability platforms.
- Enterprise cloud transformation, production AI/ML environments, and mission-critical or regulated platforms.
- Strong coordination with architecture, operations, security, and delivery teams. Python is mandatory. Relevant technologies include GenAI, LLMs, RAG, AgentCore, MCP, AWS Bedrock, SageMaker, vector databases, model lifecycle management, and AWS/Azure/GCP. Experience with engineering copilots such as Kiro or GitHub Copilot is relevant. Infrastructure automation, CI/CD, Kubernetes, Docker, service meshes, and tools such as Terraform, Datadog, Dynatrace, Splunk, Prometheus, and OpenTelemetry are useful. JD4: AI Architect / FDE – Healthcare This role focuses on AI-enabled enterprise architecture, GCP engineering, and integration in a healthcare environment. 12+ years of overall IT experience, with substantial cloud, enterprise, integration, or AI/ML architecture experience.
- Strong hands-on GCP and cloud-native architecture.
- Vertex AI, GenAI solution design, prompt engineering, model integration, governance, and production deployment considerations.
- Strong Java and Spring Boot, including microservices, REST APIs, security, and scalable backend design.
- Enterprise integration connecting modern and legacy platforms.
- Ability to evaluate and apply AI productivity tools such as Claude and Antigravity.
- Healthcare, clinical operations, payer/provider integration, regulated environments, and relevant Google Cloud certifications are preferred. GCP/Vertex AI and Java/Spring Boot are central requirements for this search. Work model: hybrid, with no fully remote option.
- Travel: approximately 25% when necessary.
- Office attendance: the exact weekly onsite schedule remains pending.
- Benefits include medical/dental/vision coverage, disability and life insurance, a 401(k) with company match, paid leave, and parental leave. A performance-based bonus is indicated, with individual terms to be confirmed. US citizens and Green Card holders are preferred. H1B transfers are possible. Candidates must be willing to join the hiring