Project Role : Custom Software Engineer
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : AI & Data Solution Architecture
Good to have skills : NA
Minimum 15 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary: Minimum 2 year experience is required in this role
Technical lead for the entire program. This person owns all architecture decisions, the AI/ML strategy, and the platform design from Day 1 through enterprise scale.
They will work alongside a small senior team and a SMEs to deliver something that does not exist anywhere in the organization today ?? a graph-native, agent-driven knowledge platform connecting every part of the engineering estate into a single query able intelligence layer.
Responsibilities
Own the full 9-layer architecture from connector ingestion through MCP Gateway to agent orchestration and the enterprise UI
Lead all Architecture Decision Records (ADRs) and design reviews, ensuring alignment with s enterprise constraints and zero-trust security posture
Design the LangGraph-based Core: the 13-node StateGraph, hybrid BM25+vector retrieval pipeline, context packer, and Bedrock model routing strategy
Architect the MCP Gateway ?? the single enforcement point for all agent tool calls ?? including per-agent RBAC, rate limiting, token budget enforcement, and full audit trail
Own the entity resolution architecture: blocking, matching, merge, and master index design across 9 heterogeneous source systems (GitHub, Confluence, ServiceNow, JIRA, CMDB, SonarQube, Dynatrace, REMC, RepoMapping)
Own the Bedrock model strategy: Haiku vs Sonnet tiering, cross-region inference profiles, PII/PCI guardrails, and RAGAS evaluation pipeline
Drive the tech stack approval process: present AWS services, open-source frameworks, and third-party MCP integrations to the architecture review board
Mentor AI native engineers conduct code and design reviews set standards for observability (OTel/ADOT), testing, and idempotent a pipeline patterns
Partner with the Product Owner to translate business use cases into architectural requirements across three pilot workstreams: AI Productivity, AI First Change, and AI First Run
Define Phase 3 enterprise patterns: SPIFFE/SVID zero-trust mesh, multi-tenant graph isolation, and the longitudinal learning loop
Required skills
Deep expertise in LLM orchestration frameworks ?? LangGraph, LangChain, or equivalent can build multi-node stateful agents from scratch
Hands-on AWS: ECS Fargate, Neptune Serverless, OpenSearch Serverless, Bedrock, ElastiCache, RDS, Secrets Manager, IAM/IRSA ?? not conceptual familiarity
Graph abase design: OpenCypher, Neptune, entity-relationship modeling across heterogeneous sources
Vector search and hybrid retrieval: embedding models, BM25, dense+sparse fusion, RAGAS evaluation
Python, FastAPI, and production-grade async service design
Security architecture: zero-trust networking, SPIFFE/SVID, mTLS, workload identity, PII/PCI guardrail design
Knowledge graph and entity resolution: blocking, matching, survivorship, master a management
OTel/ADOT end-to-end instrumentation and distributed tracing
Terraform or AWS CDK for infrastructure-as-code at scale
Ability to lead technical approval processes with enterprise architecture review boards
Experience presenting complex technical strategy to executive and business stakeholders
Qualification 15 years full time educationSourced from naukri
