Top Tech Jobs & Startup Jobs in Chennai

Conduct outbound cold calls, email, and LinkedIn campaigns to target international prospects. Present consulting and digital engineering services, engage decision-makers, qualify opportunities, schedule meetings, follow up with interested prospects, coordinate pre-sales discussions with technical teams, and document sales activity in Salesforce CRM.

Own digital marketing and qualified web lead generation, focusing on SEO, AEO, website performance, analytics, CMS management, content syndication, and conversion optimization. Manage GA4, Search Console, Tag Manager, Looker Studio, and SEO tools; improve rankings, AI search visibility, Core Web Vitals, landing pages, and lead funnels. Run A/B tests, monitor attribution and conversion quality, and collaborate with content, campaign, design, and development teams.

Lead design, development, and deployment of production-grade LLM and RAG-based AI solutions. Improve retrieval performance, build automated evaluation and validation frameworks, instrument pgvector retrieval KPIs, integrate metrics into CI/CD, and mentor mid-level engineers while driving technical reviews and best practices.

Leads the architecture, development, deployment, and governance of enterprise AI systems, including LLM applications, multimodal models, RAG, and multi-agent solutions. Drives prototyping through production delivery, establishes LLMOps practices such as CI/CD, observability, evaluation, and model versioning, and supports presales strategy. Collaborates with product and data teams, ensures security and privacy compliance, and mentors junior engineers.

Lead architecture for enterprise AI initiatives across products, platforms, and shared capabilities. Define AI architecture standards, reference patterns, governance, security, and operational guardrails. Guide solutions involving LLM applications, retrieval systems, agentic workflows, orchestration, evaluation, observability, and cloud-native platforms. Partner with business, product, and engineering leaders, influence strategic decisions, mentor technical teams, and support AI-enabled software development and platform modernization.

Lead the design, development, and delivery of scalable web applications using Node.js, TypeScript, React, AWS, Docker, and Kafka. Drive architecture, engineering standards, testing, CI/CD, cloud deployment, and quality practices. Mentor junior and mid-level engineers, collaborate with DevOps and cross-functional teams, and participate in technical hiring and interviews.

Design and maintain scalable Python microservices, REST APIs, WebSockets, background jobs, and event-driven systems. Deploy AWS infrastructure using Terraform or AWS CDK, build CI/CD pipelines, optimize PostgreSQL, DynamoDB, and Redis data layers, and enforce secure authentication and access controls. Develop frontend features with React, Next.js, and TypeScript, while integrating AI/LLM capabilities, agentic frameworks, RAG workflows, and vector databases. Lead backend architecture and ensure quality through automated testing and LLM evaluations.

Design, develop, test, and deploy MuleSoft API-led integrations connecting Salesforce with external platforms, warehouses, Anaplan, and partner systems. Lead data transformation, event-driven integrations, security, API governance, and contract design. Conduct technical workshops, gather requirements, document solutions, coordinate with stakeholders and vendors, and independently own integration initiatives through production deployment and post-launch support.

Design and implement complex web applications, improve engineering and quality standards, create CI/CD pipelines, support technical hiring, and coach junior and mid-level engineers. The role requires advanced Node.js development, TypeScript and React, database querying, testing, Docker-based deployment, AWS infrastructure configuration, and Kafka knowledge.

Lead QA automation initiatives by architecting frameworks, migrating automation suites to Playwright, and developing UI and API tests. Integrate testing into CI/CD pipelines, define quality metrics, maintain testing infrastructure, document standards, conduct peer reviews, assess product quality, mitigate testing risks, and provide technical guidance and onboarding for QA teams.