4491 - AI engineering Lead

Innovaccer
Noida
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 6+ yearsEducation: mastersSkills: ["Communication","Customer focus"]

Lead the end-to-end engineering of agentic and RAG systems in production, owning architecture, evaluation, deployment, and the latency/cost profile. Collaborate with product and customer teams to frame problems, define workflows, and improve retrieval quality and reliability. Drive LLMOps with versioning, CI evals, observability, and safety guardrails, while selecting and optimizing models (fine-tuning, LoRA/QLoRA, quantization, serving). Grow and mentor a small engineering team.

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FursaFursa
Innovaccer
Innovaccer
20 hours ago

4491 - AI engineering Lead

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 38 minutes agoStatus: Live

Job Summary

Lead the end-to-end engineering of agentic and RAG systems in production, owning architecture, evaluation, deployment, and the latency/cost profile. Collaborate with product and customer teams to frame problems, define workflows, and improve retrieval quality and reliability. Drive LLMOps with versioning, CI evals, observability, and safety guardrails, while selecting and optimizing models (fine-tuning, LoRA/QLoRA, quantization, serving). Grow and mentor a small engineering team.
Location: Noida
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Manager level

Key Responsibilities

  • •Architect and design production agentic and RAG systems that meet customer scale and reliability requirements.
  • •Own retrieval pipelines end to end, including chunking, embeddings, vector stores, re-ranking, and relevance tuning.
  • •Run the LLMOps lifecycle: model/prompt versioning, CI eval pipelines, observability (tracing, token and cost dashboards), and release guardrails.
  • •Select, fine-tune, and serve SLMs/open models, applying LoRA/QLoRA, quantization, and inference optimization with serving trade-offs.
  • •Define and execute the quarterly roadmap, set coding/evaluation standards, and lead design reviews while growing a small team.

Pay and Benefits

Perks:Paid LeaveParental LeaveSabbatical LeaveHealth InsuranceChildcarePet Friendly

Key Requirements

  • •6+ years in data science, applied ML, or AI engineering, including 2+ years building LLM-powered products.
  • •Deep NLP and GenAI experience, with strong applied ML foundations.
  • •Strong hands-on Python for scalable, performant enterprise applications and optimization.
  • •Hands-on experience with deep learning frameworks such as PyTorch and/or HuggingFace transformers.
  • •At least one shipped GenAI product with complex architecture (multiple agents, memory, retrieval, and production tracing/evaluation).
Experience:6+ years
Education:Master's
Skills:CommunicationCustomer focus
Tech Stack:PythonPyTorchHuggingFace TransformersLoRAQLoRAPEFTDatabricksAzure MLSageMakerLangGraphLlamaIndexCrewAIDockerRESTGRPCFastAPIDjangoOpenTelemetryOTELVector stores

Company Brief

Innovaccer
Provides a healthcare data activation platform that unifies clinical, claims, and operational data to enable analytics, care management, population health, and value-based care initiatives for providers, payers, and life sciences organizations.
Industry: HealthTech
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series D
Headquarters: San Francisco, United States
Founded: 2014
WebsiteLinkedIn