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 : Java Full Stack Development
Good to have skills : NA
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education
Role Summary
Lead the design and delivery of agentic AI solutions—composable, multi agent systems that integrate LLMs, RAG pipelines, vector databases, and enterprise APIs—so teams can move from automation to autonomy across business workflows.AI Powered Tech Talent
Outcomes & Responsibilities
Architecture & Patterns
o Define end to end agentic architectures (orchestration, planning, tool use, memory, evaluation loops), and publish reusable reference designs and patterns for multi agent workflows.
o Standardize components: LLM providers, embedding models, vector DBs, retrieval strategies, prompt templates, evaluators, and observability stacks.
Solution Design & Delivery
o Translate business problems into practical AI solutions lead discovery, scoping, PoC, pilot, and scale out phases with clear communication to business and engineering stakeholders.
o Own non functional requirements: security, privacy, compliance, performance, reliability, and cost efficiency (incl. token/compute budgeting).
Data & RAG
o Establish data contracts and retrieval patterns (chunking, indexing, hybrid search, citations/grounding, freshness). Design guardrails to minimize hallucinations and enforce factuality.
Platforms & Integration
o Define integration strategies with enterprise systems, event streams, APIs/gateways, and CI/CD ensure alignment with SDLC and release governance.
Quality & Responsible AI
o Set evaluation frameworks (offline/online), E2E telemetry, failure modes/mitigations, and safety policies for content, access, and action boundaries.
Leadership
o Guide squads of developers contribute to internal enablement (playbooks, training tracks, coding standards). Support interviewer panels for AI native hiring.
Must Have Qualifications (AI Native archetype)
Strong CS and software engineering fundamentals.
Hands on experience with LLMs, RAG, vector DBs, and AI APIs.
Proven ability to build end to end applications and integrate AI into systems.
Visible portfolio of AI projects demonstrating experimentation and speed.
Fast learner with a bias for rapid prototyping and iteration.
Able to translate business problems into practical AI solutions with clear communication.
Programming Languages (Architect)
Primary proficiency (at least one):
o Python (fast prototyping, LangChain/LlamaIndex, eval harnesses)
o TypeScript/Node.js (agent orchestration in services, API tooling)
o Java (enterprise integration, microservices, performance)
Secondary/beneficial: C#/.NET, Go, Rust (for performance critical agents or tooling), SQL (PostgreSQL/pgvector), Shell scripting (DevOps automation).
Ecosystem familiarity: LangChain, LlamaIndex, Semantic Kernel vector DBs (pgvector, Pinecone, Weaviate, Milvus) messaging (Kafka/JMS) API gateways cloud SDKs (Azure/AWS/GCP).
Preferred Skills & Experience
Designing multi agent systems (planner/executor roles, collaboration protocols, tool abstraction) experience with agent frameworks or custom orchestration.
Production grade RAG (retrieval evaluators, re ranking, freshness pipelines), vector DBs, and hybrid search.
LLMOps/ModelOps: prompt/versioning, eval harnesses, feature flags, canarying, A/B testing, safety gateways.
Cloud native architecture (containers, serverless, events), secrets management, policy as code, and cost governance for AI workloads.
Enterprise integration: API gateways, event buses, messaging (JMS/Kafka), and contract testing.
Additional Information:
- The candidate should have minimum 12 years of experience in Java Full Stack Development.
- A 15 years full time education is required.
