Top Artificial Intelligence Jobs in Chennai

Lead Android platform architecture and AOSP-based custom ROM development for an AI-native phone. Define OS-level AI integration, system services, privileged APIs, permissions, security architecture, and platform extensions. Partner with hardware vendors and ODMs on device integration, assess technical trade-offs, and establish engineering standards. The role requires deep Android internals expertise, platform-level feature delivery, ROM modification experience, and strong Java, Kotlin, and C++ skills.

Develop and modify Android Framework components, system services, privileged APIs, and secure AI-agent integrations. Work on application lifecycle, permissions, background execution, first-party app integration, OS stability, and performance while collaborating with agent engineers. Requires strong Android, Java or Kotlin, AOSP, Binder IPC, permissions, and complex debugging experience.

Design AI-native experiences for everyday phone use, including proactive interactions, voice, touch, conversational interfaces, contextual workflows, and transparent agent actions. The role involves prototyping and validating new interaction models while collaborating closely with product and engineering teams. Candidates should have strong product and interaction design experience, mobile or complex workflow design expertise, prototyping skills, usability knowledge, and strong product thinking.

Seeking senior software engineers with proven expertise in at least one technical area, including AI/ML, LLMs, data, full-stack or backend development, automation, cloud infrastructure, and DevOps. Responsibilities include solving complex problems independently, collaborating across technologies, and delivering production-quality projects in a startup environment. Engagements may be project-based or ongoing.

Lead production AI initiatives including LLM agents, AI drafts, and a shared Context Engine. Own architecture decisions, evaluation systems, guardrails, observability, reliability, and quality measurement. Deliver major AI projects from design through production while providing cross-functional technical leadership and improving engineering standards. Build backend and platform infrastructure using Python, Django, PostgreSQL, Redis, asynchronous workers, and REST or GraphQL APIs.

Lead enterprise AI enablement initiatives spanning AI strategy, tool evaluation, workflow automation, product and agent development, testing, rollout, adoption, documentation, and upskilling. Partner with technology, product, compliance, IT, vendors, and business teams to assess AI tools, develop solutions, guide responsible usage, and deliver measurable business impact.

Designs and maintains a centralized AI platform and agentic framework supporting secure deployment, management, and integration of AI agents. Responsibilities include building scalable agentic solutions, developing unified APIs, integrating agents into applications, optimizing cloud-native workloads, ensuring security and compliance, conducting capacity planning, mentoring engineers, and shaping the platform roadmap.

Designs, develops, administers, and supports enterprise AI solutions using Microsoft Copilot, Claude, and Azure AI Foundry. Leads AI orchestration, prompt and workflow optimization, RAG implementations, platform integrations, MCP deployments, automation, security configuration, monitoring, upgrades, and issue resolution. Partners with stakeholders and IT teams, leads AI projects, documents workflows, and ensures responsible AI practices, compliance, and service-level performance.

Design and deliver production AI solutions for enterprise customers, including agentic AI systems, LLM applications, RAG pipelines, ML services, APIs, and LLMOps infrastructure. Lead technical customer engagements, pre-sales initiatives, architecture decisions, delivery workstreams, and escalations. Collaborate with engineering and product teams, deploy solutions across cloud and on-premises environments, establish responsible AI controls, and mentor junior engineers while ensuring measurable business outcomes.

Design, develop, and maintain scalable enterprise applications using Java, Spring Boot, microservices, APIs, and cloud-native technologies. Collaborate with cross-functional teams to deliver secure, reliable, high-performance solutions for business-critical needs.

Build intelligent, user-centric web applications powered by AI and Generative AI. Combine front-end engineering expertise with AI/ML integration to create modern digital products and next-generation user experiences. Collaborate with Product Managers, UX Designers, Data Scientists, and Backend Engineers throughout product development.

Designs, implements, and optimizes Microsoft 365 security, compliance, identity, data governance, and AI-agent controls. Configures Purview, Entra ID, Defender, DLP, retention, eDiscovery, Conditional Access, MFA, RBAC, and privileged access. Assesses client environments, identifies gaps, develops remediation plans, and delivers technical documentation, workshops, testing, implementation, and knowledge transfer. Requires strong consulting, customer-facing, documentation, and PowerShell automation skills.

Design, build, and lead scalable backend services and AI platform systems using Node.js, TypeScript, AWS, databases, and modern LLMs. Own architecture, reliability, security, observability, CI/CD, and performance across multiple teams. Mentor engineers, guide technical direction, collaborate cross-functionally, and ship agentic AI products in a startup environment. The role remains hands-on, covering distributed systems, APIs, cloud infrastructure, and end-to-end solution design.

Lead the development, training, deployment, and maintenance of machine learning and generative AI systems. Build predictive, NLP, chatbot, LLM, and agentic AI solutions using cloud platforms, big data technologies, databases, and ML frameworks. Design ETL pipelines, optimize data processing, and create analytics visualizations. The role also involves model fine-tuning, scalable AI application development, and collaborative problem-solving.

Design and implement quality engineering strategies for AI-powered applications, LLMs, RAG pipelines, copilots, and autonomous agents. Build scalable Python automation frameworks, AI evaluation pipelines, synthetic datasets, and validation workflows. Test APIs, microservices, distributed systems, and agent orchestration while integrating quality gates into CI/CD. Validate vector databases, model behavior, safety, observability, reliability, performance, and cloud deployments across Docker, Kubernetes, and major cloud platforms.

Design, develop, and deliver scalable full-stack applications using .NET Core, C#, Angular or React, APIs, microservices, Azure, Docker, and CI/CD. Use AI-assisted coding tools and prompt engineering to improve development, testing, debugging, and automation workflows. Implement secure authentication, authorization, and cloud-native deployments while applying clean architecture, TDD/BDD, and strong testing practices. Collaborate with clients and cross-functional teams to translate requirements into reliable technical solutions and own delivery.

The posting provides no specific responsibilities, qualifications, compensation, location, travel, or clearance details. The title indicates a Generative AI engineering role focused on AWS technologies.

Lead end-to-end AI research, development, evaluation, and production deployment for ecommerce search, retrieval, ranking, personalization, computer vision, and multimodal discovery. Build and optimize multimodal models and pipelines, establish evaluation and MLOps practices, and deliver GenAI and agentic systems. Provide technical leadership through architecture decisions, mentoring, research direction, and cross-functional collaboration while ensuring scalable, reliable, observable, and cost-efficient ML operations.

Design AI-assisted enterprise experiences by conducting user research, mapping journeys, creating conversational workflows, prompts, wireframes, prototypes, and service blueprints. Apply design thinking, service design, accessibility, inclusive design, and responsible AI principles. Collaborate with business, product, technology, and adoption teams to integrate experience design into solution delivery, then iterate based on usability and adoption feedback.

Build and manage Azure Databricks jobs, lakehouse pipelines, reusable Python/PySpark scripts, and cloud-native microservices. Develop LLM-powered copilots, agentic workflows, RAG pipelines, prompt strategies, guardrails, and AI inference services. Integrate enterprise data with AI solutions, optimize performance and costs, implement governance and observability, and contribute to architecture and technical design. The role also involves independent ownership, code reviews, mentoring, stakeholder collaboration, and delivering production-grade AI solutions.

Leads clinical systems teams and oversees RPA, system integration, and AI/ML projects. Ensures study goals, timelines, quality standards, client requirements, and contractual obligations are met. Provides technical support, escalation management, contingency planning, resource utilization oversight, and people leadership, including coaching, performance management, interviewing, and mentoring. Supports customer relationships and delivery teams while managing junior professionals.

Build and operate production backend services supporting Supabase AI products, including the MCP server. Responsibilities include service architecture, deployments, scaling, authentication and authorization, observability, reliability targets, on-call incident response, rate limiting, capacity management, and API evolution. The role requires strong TypeScript or Go skills, production backend experience, distributed-systems debugging, and collaboration with Platform and SRE teams in a fully remote environment.

Owns Athena’s organization-wide data governance, privacy, protection, and responsible AI framework across multiple countries. The role develops policies, consent and risk tools, data inventories, compliance processes, incident response, AI approvals, and ISO 27001/SOC 2 readiness. It also trains staff and partners, supports live projects, manages audits, advises clients and regulators, and reports governance progress to leadership.

Lead pre-sales and technical delivery for Microsoft Industry Solutions, mapping customer needs to Microsoft Cloud and AI solutions. Drive project planning, risk mitigation, stakeholder engagement, IP reuse, and business development while mentoring teams and ensuring operational compliance.

Own the APAC partner marketing strategy and budget, developing joint marketing plans with VARs, TSDs, BPOs, and GSIs. Execute integrated digital, hybrid, and in-person programs that generate demand, create and accelerate pipeline, and support revenue growth. Align Partner Sales and Marketing stakeholders, manage strategic relationships, establish performance metrics, report ROI, and optimize investments across the region.