Senior Custom Software Engineer - AI & Full Stack Development

Accenture India Private Limited; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Accenture India Private Limited in Bengaluru is seeking a Custom Software Engineer to design, code, and enhance components across systems using modern frameworks and agile practices. Strong emphasis on Java full-stack development and AI-enabled capabilities.

The role leads the design and delivery of agentic AI solutions, including architecture definition, tooling standardization, and collaboration with business and engineering stakeholders to achieve scalable, secure, and cost-efficient outcomes.

Qualifications

• Strong CS and software engineering fundamentals.
• Hands on experience with LLMs, RAG, vector DBs and AI APIs.
• Proven ability to build end-to-end AI-enabled applications.

Responsibilities

• Define end-to-end agentic architectures and publish reusable designs.
• Standardize components: LLM providers, embeddings, vector DBs and prompts.
• Translate business problems into practical AI solutions from PoC to scale.
• Own non-functional requirements: security, privacy, performance, cost.
• Establish data contracts and retrieval patterns for RAG pipelines.
• Define integration strategies with enterprise systems and APIs.

Skills

Java Full Stack Development

LLMs & AI APIs

Strong CS Fundamentals

Education

15 years full time education

Tools

LangChain

LlamaIndex

Vector DBs

API orchestration

Job description

Custom Software Engineer 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
  • Define end to end agentic architectures (orchestration, planning, tool use, memory, evaluation loops), and publish reusable reference designs and patterns for multi agent workflows.
  • Standardize components: LLM providers, embedding models, vector DBs, retrieval strategies, prompt templates, evaluators, and observability stacks.
• Solution Design & Delivery
  • Translate business problems into practical AI solutions lead discovery, scoping, PoC, pilot, and scale out phases with clear communication to business and engineering stakeholders.
  • Own non functional requirements: security, privacy, compliance, performance, reliability, and cost efficiency (incl. token/compute budgeting).
• Data & RAG
  • Establish data contracts and retrieval patterns (chunking, indexing, hybrid search, citations/grounding, freshness).
  • Design guardrails to minimize hallucinations and enforce factuality.
• Platforms & Integration
  • Define integration strategies with enterprise systems, event streams, APIs/gateways, and CI/CD ensure alignment with SDLC and release governance.
• Quality & Responsible AI
  • Set evaluation frameworks (offline/online), E2E telemetry, failure modes/mitigations, and safety policies for content, access, and action boundaries.
• Leadership
  • 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):

• Python (fast prototyping, LangChain/LlamaIndex, eval harnesses)
• TypeScript/Node.js (agent orchestration in services, API tooling)
• 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.