Top Tech Jobs & Startup Jobs in Chennai

Designs, develops, tests, and deploys production-grade Agentic AI and Generative AI applications. Responsibilities include building RAG pipelines, agent workflows, knowledge retrieval systems, reusable AI modules, and cloud deployments. The role also involves data preprocessing, feature engineering, model optimization, API integration, performance troubleshooting, and collaboration on scalable AI solutions using modern LLM and orchestration technologies.

Leads enterprise BI projects using Power BI and Microsoft Fabric, including BI strategy, dashboard and data-model development, delivery oversight, team management, and stakeholder engagement. Ensures reporting quality, data governance, security, warehousing, and ETL standards while supporting business decision-making. The role requires advanced expertise in DAX, Power Query, SQL, and data modeling, with exposure to Azure Data Factory, Looker, Python, and R.

Own end-to-end enterprise architecture across AWS and Azure environments, establishing scalable, secure, reusable integration patterns for GenAI, chatbot, translation, and document-processing services. Define target-state architecture, review designs, resolve integration constraints, lead architecture governance, and establish non-functional requirements covering security, data residency, exactly-once processing, and disaster recovery.

Lead complex technical programs spanning software development, cloud platforms, AI/GenAI, automation, and platform engineering. Own planning through production deployment, coordinate cross-functional engineering teams, facilitate architecture and technical decisions, manage scope, schedules, budgets, risks, quality, and dependencies, and oversee Agile delivery. Partner with executives, customers, vendors, architects, and engineering leaders while driving governance, release readiness, security, compliance, and continuous delivery improvements.

Own technical testing of AI agent outputs by building validation suites against golden-record datasets, tracking accuracy and turnaround-time metrics, and performing regression testing after agent or prompt changes. The role supports regulated-process quality assurance by providing technical evidence and findings for human QA sign-off. Candidates should have substantial QA or test engineering experience, including validation of ML or LLM outputs and benchmark dataset development for document or text-processing systems.

Build and deploy regulated-process AI agents on AWS Bedrock, including document generation, validation, and case intake workflows. Develop Fargate services, integrate Microsoft Graph API and event-driven patterns, configure prompts and guardrails, and test agent performance. Own OCR and intelligent document-processing pipelines using AWS Textract or equivalent and Azure Document Intelligence. Improve extraction accuracy, support auditability, integrate third-party tooling, and collaborate with QA and compliance teams.

Develop, test, and deploy generative AI agents and document-processing pipelines using AWS Bedrock and Fargate. Build OCR and intelligent document processing workflows, integrate Microsoft Graph API and enterprise platforms, engineer prompts and guardrails, and improve extraction accuracy and agent performance. Collaborate with architects, QA, and business stakeholders to deliver secure, compliant, production-ready AI automation for regulated and semi-regulated processes.

Provisions and operates AWS infrastructure supporting agent services, including VPCs, Fargate clusters, messaging, storage, monitoring, and observability. Manages infrastructure as code for repeatable deployments, ensures reliable exactly-once processing, coordinates security and access approvals for regulated client environments, and supports resilient multi-site delivery across AWS and Azure AI services.

Provide US-focused HR shared services across HR Operations, Payroll, Compensation & Benefits, Talent Management, and Ask HR. Manage employee lifecycle activities, resolve complex employee cases, maintain HR data in HRIS, support enterprise HR systems, collaborate with stakeholders, identify process improvements, and mentor junior staff (for Lead).

Provide customer support via phone, email, chat and social media; resolve inquiries, meet contact-center SLAs and satisfaction targets; complete required training, follow data-security/NDAs, attend coaching, and maintain perfect schedule adherence.