Top Artificial Intelligence Jobs in Chennai

Lead visual design across client websites, product interfaces, and brand identities from concept through delivery. Use AI tools for ideation and iteration while art-directing outputs to maintain distinctive quality. Build scalable design systems, collaborate with project leads and clients, defend design decisions, and adapt desktop-first designs for mobile. The role also requires staying current with visual design and AI tooling trends.

Participate in full-stack development and maintenance of Binance’s KYC system, including backend services, frontend features, documentation, testing, regression, troubleshooting, and customer issue resolution. The role is a 3–6 month accelerator internship for current university students and recent graduates, with an emphasis on Java, Spring Boot, databases, middleware, and frontend technologies.

The AI SEO Analyst develops and executes technical, on-page, off-page, and local SEO strategies across content types. Responsibilities include keyword research, metadata and schema optimization, AI prompt refinement, review of AI-generated content, ranking and traffic analysis, performance reporting, and workflow improvement. The role collaborates with editors, strategists, and developers, supports junior team members, maintains prompt libraries, and works a 7:30 PM to 4:30 AM IST night shift in Chennai.

Curate and correct researcher profiles, authorship records, affiliations, publication metadata, and journal information for Web of Science. Validate AI-suggested authorship matches, investigate customer profile issues, apply editorial policies, perform research and metadata corrections, and maintain quality and productivity standards.

Leads customer-facing AI transformation initiatives from business discovery through solution architecture and implementation. Designs scalable AI workflows, agents, integrations, and enterprise solutions using DevRev’s platform. Partners with customers, sales, customer success, engineering, and product teams to translate requirements into measurable outcomes. Supports pre-sales, oversees delivery with Applied AI engineers, drives reusable architecture, and ensures performance, security, and compliance. Requires extensive travel for implementations, workshops, and customer engagements.

Leads end-to-end certification, compliance, and testing for RuPay cards, 3DS, tokenization solutions, and payment applications. Executes test cases, manages defects, resolves certification issues with banks and payment partners, maintains audit documentation, and supports automation. Coordinates multiple certification activities across internal teams and external stakeholders while ensuring alignment with NPCI standards and industry best practices.

Develop AI applications using Python, generative AI, LLMs, RAG, vector databases, APIs, and agentic AI frameworks. Build and integrate solutions with models including GPT, Claude, Gemini, and Llama. Use LangChain, LangGraph, Docker, cloud platforms, and modern deployment tools. The role requires strong problem-solving, API development, prompt engineering, and immediate or short-notice availability for office-based work.

Develop and implement LLM-driven generative AI solutions using agentic AI, multi-agent systems, RAG, Python, vector databases, OpenAI, Gemini, LangChain, and Hugging Face. The role requires hands-on GenAI experience and involves working hybrid in Chennai, four days per week onsite, during an 11 AM to 8 PM shift.

Lead enterprise Agentic AI and data architecture, including multi-agent systems, RAG platforms, AI governance, MLOps, cloud AI integrations, and scalable data architectures. Establish standards for model lifecycle management, security, evaluation, monitoring, and responsible AI. Mentor technical teams, guide AI modernization initiatives, evaluate emerging technologies, and influence long-term enterprise AI, data, and analytics strategy.

Develop production-grade AI-enabled platform capabilities, APIs, backend services, integrations, and reusable software enhancements. Build model integrations, prompt and retrieval workflows, extraction logic, and agent configurations while ensuring scalability, security, reliability, testing, observability, and maintainability. Collaborate with Product, Solution Engineering, Application Engineering, Platform Reliability, and Architecture teams to translate requirements into customer-facing platform solutions. Contribute to CI/CD, automated testing, deployment, documentation, and responsible AI practices.

Lead applications development teams while designing, developing, and deploying scalable Generative AI solutions. Build Python backend services, integrate GenAI APIs, implement RAG systems, optimize application security and performance, and ensure testing and code quality. Responsibilities also include technical oversight, hiring and personnel management, resource allocation, risk and compliance management, budget participation, and cross-functional collaboration.

Lead and manage applications development teams while designing, developing, and deploying scalable Generative AI solutions. Build Python backend services, integrate GenAI APIs, implement RAG systems, and optimize application performance, scalability, and security. Oversee technical solutions, staffing, delivery, budgets, risk, compliance, testing, code reviews, and engineering standards. Collaborate with product managers, data scientists, and engineers to deliver reliable AI-powered products.

Architect and develop production-grade generative and agentic AI systems using foundation models, RAG, knowledge graphs, multi-agent orchestration, and context engineering. Build reliable agent harnesses with governance, observability, security, and interoperability protocols. Integrate AI applications into scalable cloud environments, optimize real-time solutions, ensure responsible AI compliance, and mentor junior engineers. The role emphasizes application architecture and orchestration rather than model training or fine-tuning.

Leads enterprise delivery of production-ready generative and agentic AI solutions. Responsibilities include architecting RAG, knowledge graph, multi-agent, and context-engineering systems; managing AI engineers; overseeing project delivery; partnering with cloud, data, and MLOps teams; implementing CI/CD, observability, governance, guardrails, and ethical AI practices; and managing stakeholders, risks, budgets, and timelines.

Architect and develop production-grade generative and agentic AI applications using RAG, knowledge graphs, multi-agent orchestration, and foundation-model APIs. Build reliable agent harnesses with governance, observability, interoperability, and safety controls. Deploy scalable AI systems using cloud infrastructure, Docker, Kubernetes, and CI/CD. Mentor engineers, conduct code reviews, collaborate with stakeholders, and advance responsible AI practices.

Own analytics and measurement for HighLevel’s AI product portfolio. Define instrumentation standards, feature-level KPIs, adoption and quality metrics, and rigorous approaches for evaluating nondeterministic AI features. Partner with experimentation leaders, PMs, engineering, and Analytics Engineering to close data gaps, influence product roadmaps, establish canonical metrics, and mentor future analysts.

Performs end-to-end certification and application testing for NPCI payment products, including executing test cases, logging and resolving defects, maintaining certification documentation, supporting audits, and implementing automation. Collaborates with banks, payment partners, vendors, and internal teams to validate products against NPCI standards before deployment. The role also supports multiple certifications, process improvement, technical documentation, and payment application troubleshooting using APIs and testing tools.

Coordinates end-to-end customer onboarding, including documentation, product certification, waivers, production readiness, milestone tracking, and audit follow-up. Collaborates with Risk, Network, and Production teams, communicates onboarding progress, resolves roadblocks, maintains CRM and tracker records, gathers customer feedback, and supports process improvement. Ensures compliance with Quality Management System standards while delivering a customer-first experience.

Build and ship AI-powered features for fashion, beauty, and home using large-scale product, image, and consumer data. Prototype with LLMs, agents, multimodal and CV models, run experiments, measure impact, and take models end-to-end from hypothesis to production while collaborating with product, design, and business teams.

Fine-tune and optimize small language models using Hugging Face, TRL, and adapter methods. Build MLOps pipelines, deploy models to edge and mobile environments, meet strict latency targets, and monitor production accuracy, latency, and hardware utilization. Evaluate model quality through benchmarking and custom evaluation suites while applying quantization, pruning, and knowledge distillation.

Lead enterprise AI platform development by defining architecture, model-serving strategy, and engineering standards. Build production-grade AI systems, scalable APIs, LLM integrations, RAG pipelines, and agentic workflows. Responsibilities include testing, documentation, deployment, optimization, team mentoring, collaboration, and continuous learning, with ownership and complexity increasing according to experience.

Join Welo Data’s Swedish AI Trainers Network as a flexible, remote contributor. Participants may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and review cultural and linguistic accuracy for AI systems. This is a talent community rather than an active opening. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Join Welo Data’s remote Kyrgyz contributor network for potential AI data projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create prompts for large language models; and review cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each assignment. This is a talent-community opportunity rather than an active job opening.

Join Welo Data’s Romanian contributor network for flexible, remote AI projects. Potential work includes annotating text, images, or audio; evaluating search results, advertisements, and chatbot responses; creating prompts; and reviewing cultural and linguistic accuracy. Applicants need native or near-native Romanian, English proficiency, digital tool comfort, attention to detail, and residence in Romania or Moldova. This is a talent network rather than an active opening, with project scope, timelines, and compensation provided when opportunities arise.

Join Welo Data’s Tamil contributor network for potential remote AI projects involving text, image, or audio annotation; search, advertising, or chatbot evaluation; prompt creation; and cultural and linguistic quality review. This is not an active opening. Projects vary in length and compensation, with details provided before each assignment.