Top Artificial Intelligence Jobs in Chennai

Build scalable Java full-stack applications, including Spring Boot microservices, REST APIs, event-driven integrations, and responsive React interfaces. Develop secure, tested, high-performance software while collaborating in Agile teams, participating in code reviews, and working with Product Owners and QA. Integrate AI/ML services and features into applications to support automation and decision-making. Preferred experience includes cloud deployment, CI/CD, Docker, Kubernetes, and modern AI platforms or LLM integrations.

Designs, builds, and deploys production AI solutions for legal and compliance workflows. Responsibilities include developing LLM, RAG, and agentic applications; creating document processing and evaluation pipelines; implementing security, governance, and audit controls; partnering with legal, IT, and data teams; and mentoring legal users on AI tools. The role requires technical leadership across software engineering, data science, legal operations, and enterprise AI infrastructure.

Leads analysis, mining, modeling, and visualization of large-scale transactional, operational, and customer data. Partners with compliance teams to prioritize analytical use cases, support regulatory requirements, improve business efficiency, and translate complex findings into actionable recommendations. Oversees multidisciplinary analysts, manages stakeholder data requests, assesses business changes, and develops analytical systems using machine learning, big data technologies, and visualization tools.

Leads enterprise AI and Generative AI solution architecture across pre-sales, proposals, RFPs, discovery workshops, demos, prototypes, and proof-of-concepts. Designs scalable LLM, RAG, agentic AI, cloud, data, and integration architectures; supports estimation, feasibility, and risk analysis. Develops reusable AI accelerators, reference architectures, thought leadership content, and innovation roadmaps while mentoring pre-sales teams and engaging executive stakeholders.

Leads AI innovation across HR SaaS products by owning the AI software development lifecycle, designing agentic and RAG systems, building prototypes, defining production specifications, guiding engineers, and improving in-house AI platforms. Responsibilities include prompt and context engineering, evaluation, monitoring, model optimization, orchestration, governance, and mentoring teams while scaling reliable AI features.

Build and operate the infrastructure, frameworks, SDKs, runtime systems, and tooling for an AI agent platform supporting ERP product teams. Develop frontend and backend systems, APIs, microservices, distributed services, cloud infrastructure, and production LLM integrations. Translate product requirements into technical solutions, ensure reliability and developer experience, contribute to architecture decisions, and mentor engineers.

Ensures the quality, reliability, and performance of AI products, model outputs, datasets, and supporting data pipelines. Responsibilities include designing AI/ML test strategies, evaluating prompts and LLM responses, detecting hallucinations and bias, validating ETL/ELT processes and dataset integrity, defining model quality metrics, automating API and data validation tests, integrating tests into CI/CD, and collaborating with engineering, data science, product, and QA teams.

The Product Manager role involves building AI and SaaS products from idea to MVP, using rapid prototyping and iteration based on feedback.

The role involves building and managing end-to-end product systems using AI-assisted tools, collaborating across teams, and rapidly iterating based on usage feedback.

The role involves providing legal guidance on global privacy and AI issues, collaborating with teams to ensure compliance, and developing scalable processes.

Build and own production-grade AI systems, including backend services, scalable APIs, LLM integrations, RAG pipelines, and agentic workflows. Responsibilities include testing, documentation, model deployment, performance optimization, collaboration, and continuous learning, with increasing ownership and complexity based on experience.

Architect scalable, low-latency AI/ML systems and real-time inference pipelines for voice, vision, and NLP applications. Lead model productionization, infrastructure and framework selection, architecture reviews, optimization, observability, and MLOps best practices. Collaborate with product, data science, and engineering teams while mentoring engineers. The role requires expertise in distributed systems, LLM inference optimization, vector databases, RAG, containerization, cloud platforms, CI/CD, edge deployment, and software architecture.

Senior Data & AI consultant responsible for designing, developing, and delivering cloud data and AI solutions on Microsoft platforms. Lead data engineering, platform modernization, ML readiness, MLOps, and Azure-based deployments while collaborating with customers and teams to drive adoption and technical excellence.

Assist in designing, training, optimizing, and deploying machine learning and deep learning solutions. Responsibilities include data preprocessing, REST API and service integration, model evaluation, fine-tuning, scalability improvements, and collaboration with data scientists, software engineers, and product managers. The role also involves generative AI work with LLMs, prompt engineering, and retrieval-augmented generation.

Design, build, evaluate, and deploy production-grade autonomous and multi-agent AI systems for cybersecurity detection and response. Develop LLM orchestration, tool use, memory, planning, RAG, evaluation, observability, and failure-recovery capabilities. Optimize agents for accuracy, latency, cost, reliability, and scalability while partnering with security researchers, platform engineers, and product teams to automate security workflows.

Design, develop, and deploy practical AI systems for education, including agentic and multi-agent architectures, RAG and multimodal solutions, and scalable Python pipelines. Optimize models for low-resource environments, improving reliability, latency, usability, observability, evaluation, and cost efficiency. Collaborate with cross-functional teams to translate education challenges into production-grade AI tools.

Owns technical direction for enterprise agentic AI solutions across application, cloud, data, and AI layers. Leads architecture decisions, deployment standards, security reviews, reusable infrastructure, CI/CD practices, and production monitoring. Mentors Forward Deployed Engineers toward independent delivery, guides design and code reviews, prototypes high-risk components, and resolves critical blockers. The role emphasizes technical leadership, scalable deployment capability, cloud cost discipline, agent evaluation, guardrails, and operational reliability rather than sustained feature development.

Join Welo Data’s remote contributor network for future AI data projects involving text, image, or audio annotation; search, ad, and chatbot evaluation; prompt creation; and cultural or linguistic accuracy review. Contributors must have native or near-native Twi fluency, English proficiency, digital tool comfort, and strong attention to detail. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Freelance remote contributors support AI language-data projects through annotation, evaluation, prompt creation, and Korean-to-Chinese machine-transliterated lyric review. Responsibilities include assessing meaning, fluency, naturalness, and accuracy; rating quality against defined criteria; correcting errors; and providing feedback to improve AI systems. Projects are task-based, flexible, and dependent on availability.

Join Welo Data’s global contributor network for flexible, remote AI data projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts for large language models; and review cultural and linguistic accuracy. Native or near-native Javanese fluency, English proficiency, digital tool familiarity, and attention to detail are required. This is a talent community rather than an active job opening.

Join Welo Data’s global contributor network for flexible, remote AI projects. Depending on skills and availability, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create prompts for large language models; and assess cultural and linguistic accuracy. Native or near-native Somali fluency, English proficiency, digital tool comfort, attention to detail, and curiosity are required. This is a talent community application, not an active job opening.

Contribute to AI data projects through language data annotation, evaluation, and instruction creation. Work remotely with flexible hours to help develop more inclusive and capable AI systems. Applicants must be native or near-native Simplified Chinese speakers living in China, Canada, the United States, or Malaysia, with fluent English, comfort using digital tools, strong attention to detail, and curiosity.

Join Welo Data’s Serbian AI contributor network for flexible, remote projects involving text, image, or audio annotation; search, advertisement, and chatbot evaluation; prompt creation; and cultural or linguistic quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation. Applicants need native or near-native Serbian fluency, English proficiency, digital tool comfort, attention to detail, and residence in Serbia, Bosnia and Herzegovina, or North Macedonia.

Join Welo Data’s remote Maltese AI contributor network. Depending on project needs, contributors annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create and test prompts for large language models; and review cultural and linguistic accuracy. Projects may last several days to weeks, with scope, timelines, and compensation provided before participation. This is a talent community rather than an active job opening.

Join Welo Data’s Arabic contributor network for potential remote AI projects involving text, image, or audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. Projects vary in duration and complexity, with scope, timelines, and compensation provided before participation. Candidates need native or near-native Arabic fluency, English proficiency, digital tool familiarity, and strong attention to detail.