Overview:

TekWissen is a global workforce management provider throughout India and many other countries in the world. The below job opportunity is to one of our clients who is a part of a trusted global innovator of IT and business services headquartered in Tokyo. We help clients transform through consulting, industry solutions, business process services, IT modernization and managed services. This client enables us to move confidently into the digital future. This client committed to Long Term success and combine global reach with local client attention to serve them in over 50 Countries.

Position: AI Engineer Advisor

Location: PAN India

Work Type: Hybrid

Job Type: Full Time

- Build complete production-grade agentic solutions, not only the agent layer.
- The engineer will work from business-process understanding through implementation, integration, testing, deployment, monitoring, and continuous improvement. Each engineer must be able to develop the surrounding application and workflow components required to make an agent useful, secure, reliable, and operable.
- Client and delivery context
- Three engineers will form the main implementation capacity of the SWAT pod and may be split across parallel business-process tracks.
- The client already has platform, security, governance, and architecture capabilities; engineers are expected to use those services and focus on delivery.
- Assignments may require agent logic, conventional backend development, data processing, integration, UI development, or workflow automation depending on the use case.
- Candidates must be comfortable learning unfamiliar tools and working across languages or frameworks when that is the best fit for the client platform.
- Primary ownership
- End-to-end implementation of agents, services, workflows, retrieval, integrations, user interfaces, tests, and operational instrumentation.
- High-quality production code that follows existing enterprise security, architecture, CI/CD, and observability standards.
- Structured evaluation, debugging, performance improvement, and production support for assigned use cases.
- Reusable modules, tool patterns, and implementation documentation for broader adoption.

Key responsibilities

- Analyze process requirements and translate them into technical stories, interfaces, agent behaviors, workflow steps, validation rules, and acceptance criteria.
- Build agents using appropriate patterns for tool use, planning, retrieval, state, memory, structured outputs, approvals,



and exception handling.
- Develop backend services, APIs, microservices, event handlers, data transformations, schedulers, and deterministic workflow components that support the agent.
- Build or integrate user-facing experiences using web, chat, assistant, or embedded application patterns where required.
- Integrate agents with enterprise systems, knowledge bases, data stores, search services, identity platforms, and approved model endpoints.
- Implement RAG and context-engineering patterns, including ingestion, chunking, metadata, retrieval, reranking, grounding, citations, and access-aware filtering.
- Write unit, integration, contract, security, and end-to-end tests; contribute to golden datasets, simulation, adversarial testing, and regression suites.
- Instrument applications with logs, traces, metrics, token and cost telemetry, tool-call visibility, and user-feedback capture.
- Deploy through existing CI/CD pipelines and support configuration, environment promotion, release validation, rollback, incident diagnosis, and remediation.
- Participate in design and code reviews, document implementation decisions, and transfer reusable patterns to other engineers.

Must-have candidate profile

- 7+ years of professional software, AI/ML, platform, or application-engineering experience with strong hands-on development skills.
- Production experience building LLM, RAG, AI assistant, agentic, intelligent workflow, or AI-enabled application capabilities.
- Strong proficiency in Python, Java, TypeScript/Node.js, or a comparable enterprise language; willingness to work across the stack.
- Solid knowledge of APIs, microservices, distributed systems, asynchronous processing, data structures, error handling, and automated testing.
- Practical understanding of prompts, tool calling, structured outputs, context windows, embeddings, retrieval, state, memory, and agent failure modes.
- Experience with containers, cloud services, CI/CD pipelines, source control, secrets, environment configuration, and application monitoring.
- Ability to debug complex failures across model behavior, prompts, tools, data, network calls,



application code, and infrastructure.
- Clear communication, ownership mindset, and ability to deliver in a fast-moving, highly technical client environment.

Preferred experience

- Experience developing MCP tools or integrating with MCP servers.
- Full-stack experience with modern web frameworks such as React, Angular, or equivalent.
- Experience with vector databases, enterprise search, graph databases, document processing, or multimodal data.
- Experience with one or more agent frameworks while retaining strong framework-independent engineering fundamentals.
- Experience with model evaluation, AI tracing, prompt and tool versioning, red-team testing, and production quality gates.
- Financial services, enterprise productivity, IT operations, identity, service management, or data-platform integration experience.
- Indicative technology exposure
- Python, Java, TypeScript/Node.js; FastAPI, Flask, Spring Boot, Express/NestJS; React or comparable UI frameworks; LangGraph, Semantic Kernel, AutoGen, LlamaIndex, LangChain, CrewAI, or equivalent; MCP; REST/gRPC/events; SQL/NoSQL; enterprise search/vector stores; Docker/Kubernetes/serverless; Git-based CI/CD; tracing and evaluation platforms. Tool equivalence is acceptable.

Mandetory Skills:

- Minimum 5+ years as an Enterprise, Solution or Business Architect
- Minimum 5+ years delivering Banking Transformation or Digital Banking programs
- Demonstrated experience architecting and implementing banking solutions on Azure and/or AWS cloud platforms.
- Strong expertise in cloud-native architecture including APIs, event-driven architecture, streaming, Lakehouse, microservices, containers, Kubernetes, serverless computing and enterprise integration.
- Practical experience designing secure AI and Agentic AI solutions using LLMs, RAG, vector databases, AI orchestration frameworks, GenAIOps/LLMOps and enterprise AI governance
- Robust Banking Domain expertise across Retail Banking, Corporate Banking, Payments, Cards, Deposits, Lending, Trade Finance, Treasury, Risk, Compliance, Customer Channels and Customer 360

TekWissen Group is an equal opportunity employer supporting workforce diversity

Disclaimer: This job description has been sourced from a public domain and may have been modified by Naukri.com to improve clarity for our users. We encourage job seekers to verify all details directly with the employer via their official channels before applying.

📌 AI Engineer Advisor (Kavaratti)
🏢 TEKWISSEN
📍 Kavaratti