Agentic AI Engineers

About Infocion

Infocion is a US-based Data & AI consulting firm delivering transformation across Life Sciences, Pharma, Biotech, and broader Healthcare Systems (HCLS). We help global clients unlock business value with next-gen AI—from advanced analytics to
Agentic AI
systems that drive automation, compliance, and growth.

Role Summary

We're building a world-class
Center of Excellence (CoE) in India
and hiring multiple hands-on
Agentic AI Engineers
to design, build, and operate production-grade multi-agent applications. You'll convert clinical and operational use cases into reliable agentic workflows, integrate with real systems (EHR/FHIR, CTMS, CRM), and ship secure solutions under healthcare-grade governance.
You will also help build our AgenticOps platform that provides orchestration, governance, and observability for safe multi-agent operations.

What You'll Do

1) Build Agentic Systems

• Design and implement
  multi-agent workflows
  (reason/plan/act) with tools, memory, and retrieval (RAG/graph) for HCLS use cases (e.g., prior auth, trial matching, patient timelines, protocol/safety narrative automation).
• Integrate with
  EHR/FHIR/HL7
  , CTMS, CRM, and other operational systems; develop robust API adapters and event pipelines.
• Engineer
  prompt/tool/policy layers
  (function calling, MCP, guardrails) for reliability, cost, latency, and safety.

2) Contribute to our AgenticOps platform

• Build platform capabilities:
  agent scheduling & orchestration
  , sandboxing/isolation,
  policy-as-code guardrails
  , red/blue-green/canary rollout, versioning, and
  rollback
  .
• Implement
  observability & governance
  : per-agent tracing, lineage/provenance, evaluation harnesses, drift/bias checks,
  audit dashboards
  , and PHI-safe logging.
• Create internal assets: reference architectures, maturity checklists,
  AgenticOps runbooks
  , and ROI calculators.

3) Models, Data, and MLOps

• Evaluate and integrate LLMs (GPT-4o, Claude 3, Gemini 2.5, Llama 3.x, OSS variants), including parameter-efficient tuning where needed.
• Implement
  RAG/knowledge orchestration
  with VectorDB/GraphDB (Pinecone, Weaviate, Milvus, FAISS, pgvector, Neo4j).
• Own CI/CD for agents and models (Docker/Kubernetes), testing, telemetry, and SLOs.

4) Delivery & Collaboration

• Turn ambiguous requirements into
  MVPs
  and production rollouts; run discovery/demos with US stakeholders.
• Mentor juniors within the India CoE; enforce engineering best practices (tests, benchmarks, postmortems).

Must-Have Qualifications (Engineer Level)

• 5–7 years
  total software/ML engineering experience, including
  2+ years
  building LLM/agentic applications in production.
• AgenticOps platform experience (required):
  1+ year
  building or operating an
  agent orchestration/governance platform
  (or equivalent hands-on experience composing multi-agent production systems) covering: scheduling, isolation,
  policy-as-code
  , evaluation gates, progressive delivery (canary/blue-green), observability, and audit/rollback.
• Hands-on with
  agent frameworks
  : Agno 2.0, LangChain (or AWS Bedrock AgentCore, Vertex AI Agents, Azure AI Foundry).
• Strong
  LLM integration & orchestration
  : prompt/program design, tool/function calling, context/memory, safety filters, MCP.
• RAG & knowledge layers
  with VectorDB/GraphDB; data ingestion, chunking, metadata, hybrid search, evals.
• MLOps & Ops
  : Docker/K8s, CI/CD, tracing/telemetry (Langfuse/OpenTelemetry/W&B), cost & latency tuning, rollback strategies.
• APIs & data plumbing
  : REST/GraphQL, Kafka/event streams; secure integration patterns.
• Awareness of
  HCLS compliance
  (HIPAA, 21 CFR Part 11, GxP) and
  PHI-safe retrieval
  design; you know what must be logged and why.
• Clear communication; ability to demo and explain trade-offs to technical and non-technical stakeholders.

Nice-to-Have

• HCLS experience (provider, payer, CRO, pharma) and standards (
  FHIR/HL7/DICOM
  ).
• Spark/Airflow, classical ML/NLP, or PV/RWE workflows.
• Exposure to
  Azure Health Data Services
  ,
  AWS HealthLake
  ,
  Google Healthcare APIs
  .
• Pre-sales support (POCs, demos, estimates) and authoring internal assets.

Core Tools & Technologies (you'll touch many of these)

• Agentic frameworks:
  Agno 2.0, LangChain; plus AWS
  Bedrock AgentCore
  ,
  Vertex AI Agents
  ,
  Azure AI Foundry
• AgenticOps (platform) concepts:
  orchestration/scheduling, circuit breakers, feature flags, canary/blue-green, policy-as-code, sandboxing & isolation, meta-evaluation gates
• LLMs:
  GPT-4o, Claude 3, Gemini 2.5, Llama 3.x; open-source selection & tuning
• Knowledge layer:
  Pinecone, Weaviate, Milvus, FAISS, Postgres + pgvector, Neo4j/Graph
• Data & integration:
  REST/GraphQL, Kafka;
  FHIR/HL7
  connectors; EHR/CTMS/CRM adapters
• Cloud & deployment:
  Docker, Kubernetes; AWS (Bedrock/SageMaker), Azure (OpenAI/Fabric), GCP (Vertex)
• Observability & ops:
  Langfuse, OpenTelemetry, Weights & Biases; agent tracing, audit dashboards
• Security & compliance:
  HIPAA, SOC 2, PHI handling, audit loggin

Compensation -

• Pre-revenue stage:
  up to $500/month retainer (deferred until first revenue), flexible 4–40 hrs/week.
• Hourly Base:
   up to
  $28/hour
• Delivery Bonus:
   up to
  $800 per project
   for on-time, high-quality delivery.
• Duration:
   Continues until successful completion of
  2–3 client projects
  .
• Post 2–3 projects:
  Eligible for full time employment with fixed salary
  ₹30

–
₹40 L / year
- Delivery Bonus:
 up to
₹1.5 L
per project.
- Annual Bonus:
 up to
₹2.5
L
(performance-based, tied to client satisfaction).
- Benefits:
 Health insurance, 15 days paid leave, PF contributions