Experience: 10-15 years
Location: Bangalore/Hyderabad/Pune/Mumbai/Delhi/NCR/Kolkata/Chennai
Core AI & ML Skills
- Hands-on experience building GenAI solutions (LLMs, RAG pipelines, embeddings, semantic search)
- Practical use of OCR and document intelligence techniques across unstructured data (PDFs, images, scanned forms)
- Strong understanding of NLP concepts (entity extraction, classification, keyword detection)
- Experience with agentic / multi‑agent architectures and workflow-based AI systems
- Ability to adapt or fine-tune models for accuracy, confidence scoring, and explainability
Architecture & System Design
- Proven ability to design end-to-end AI platforms, beyond proof-of-concepts
- Experience with large-scale document pipelines (ingestion → processing → indexing → retrieval)
- Strong knowledge of RAG vs alternative architectures (hybrid search, knowledge graphs, semantic indexing)
- Experience with event-driven and serverless patterns for scalable processing
- Ability to reason about trade-offs (accuracy vs cost, latency vs scale, complexity vs maintainability)
Cloud & Platform Engineering
- Strong experience in at least one major cloud platform (AWS preferred)
- Familiarity with:
- Object storage (e.g. S3)
- Serverless compute (e.g. Lambda)
- Managed AI/ML and OCR services
- Infrastructure-as-Code mindset (e.g. Terraform or equivalent)
- Ability to design cloud-agnostic solutions where required
AI‑Augmented Engineering (Prompt Coding & AI Pairing)
- Strong ability to use prompt engineering / prompt coding to generate, debug, and accelerate production-quality code
- Demonstrated capability to pair-program effectively with AI tools, iterating prompts and validating outputs
- Ability to apply judgement on when to rely on vs avoid AI-generated code, especially for security or critical logic
- Experience integrating AI into engineering workflows (test generation, documentation, code reviews)
- Maintains strong engineering fundamentals and code quality standards while leveraging AI as a productivity multiplier
MCP AI Integration (Model, Context, Platform Integration)
- Experience integrating AI models into enterprise systems using API-first and service-oriented architectures
- Ability to design model orchestration layers that connect LLMs, tools, data sources, and workflows (e.g. retrieval systems, APIs, event streams)
- Strong understanding of context injection patterns (prompt construction, metadata enrichment, grounding, tool usage)
- Experience building scalable integration pipelines between AI services and enterprise platforms (e.g. ECM systems, data lakes, APIs)
- Awareness of security, governance, and compliance controls in AI integration (PII handling, access control, audit logging, isolation boundaries)
Production Readiness & Operations
- Clear understanding of production-ready AI systems, including:
- Monitoring and alerting
- Reliability and resilience
- Scalability and performance
- Observability and runtime support
- Experience integrating into CI/CD and DevSecOps pipelines
- Awareness of security scanning, vulnerability management, and secure deployments
Responsible AI & Risk Awareness
- Strong grounding in responsible AI principles, including:
- Governance and auditability
- Explainability and transparency
- Bias and fairness considerations
- Human-in-the-loop controls
- Experience working in regulated or high-risk environments
- Ability to design solutions with compliance and audit requirements in mind
Cost & Performance Optimisation
- Ability to design for cost-efficient AI usage, including:
- Model selection and tiering
- Caching and reuse strategies
- Routing tasks to appropriate model complexity
- Awareness of token usage, OCR costs, and scaling cost drivers
- Experience implementing logging, metrics, and cost observability
Engineering & Delivery Skills
- Strong Python development skills and familiarity with AI/ML ecosystems
- Ability to deliver end-to-end solutions (POC → MVP → production)
- Experience working in cross-functional engineering teams
- Comfortable operating as a senior individual contributor with architectural influence
Communication & Collaboration
- Ability to explain complex AI systems to technical and non-technical stakeholders
- Comfortable collaborating with platform, security, and compliance teams
- Balances hands-on delivery with design leadership
Pay: ₹2,000,000.00 - ₹5,500,000.00 per year
Work Location: In person
