AI Developer

Enterprise’s interview process typically starts with a timed online coding test covering data structures, algorithms and basic aptitude. Successful candidates move to a technical interview where they discuss system design, AI/ML pipelines, and may be asked to write code on a shared editor. The final HR round focuses on cultural fit, career aspirations and compensation expectations. Preparation should include hands‑on projects with LLMs, RAG pipelines, and a solid grasp of security best practices.

Enterprise promotes a learning‑first culture with regular hackathons, internal AI forums, and mentorship programs. Employees enjoy a balanced work‑life schedule, flexible remote days, and clear growth tracks that reward performance and innovation.

B.Tech or equivalent engineering degree (Computer Science, Information Technology, Electronics, or related streams). Minimum 60% aggregate (or CGPA 6.5/10). No active backlogs at the time of joining. Graduation batch should be 2020 or later. Candidates must have 5+ years of relevant experience in enterprise software development, AI/ML, or cloud‑native microservices.

Round 1: Online coding & aptitude test → Round 2: Technical interview (system design, AI/ML concepts, coding) → Round 3: HR interview (cultural fit, expectations)

Enterprise is a global technology services firm that helps Fortune 500 companies accelerate digital transformation. With a strong focus on AI, cloud, and automation, Enterprise has built a reputation for delivering end‑to‑end solutions that combine deep domain expertise with cutting‑edge engineering. The company operates across multiple verticals including finance, manufacturing, and telecom, and maintains development centers in major Indian tech hubs such as Bangalore, Hyderabad, and Pune. Its culture emphasizes continuous learning, collaborative problem‑solving, and a commitment to responsible AI, making it an attractive destination for engineers who want to work on large‑scale, impact‑driven projects. The role of Enterprise AI Developer sits within the AI Lab, a specialised unit that designs, builds and operationalises generative AI products for internal and external clients. Reporting to the Head of AI Engineering, the incumbent will be responsible for turning proof‑of‑concept ideas into production‑grade services that automate repetitive IT support tasks, integrate with enterprise back‑ends like SAP and JIRA, and deliver self‑healing capabilities. This position requires a blend of strong software engineering fundamentals, hands‑on experience with large language models, and a solid understanding of security and compliance for AI workloads. Key responsibilities include: 1. Design, develop and deploy end‑to‑end Generative AI use cases from PoC to production, focusing on L1 support automation and L0 self‑healing infrastructure. 2. Build Retrieval‑Augmented Generation (RAG) pipelines using vector databases such as pgvector, Pinecone or custom S3‑backed stores. 3. Create robust REST and gRPC APIs that connect conversational agents to SAP web services and ticketing platforms like JIRA and BMC Helix. 4. Implement the Model Context Protocol (MCP) and other agentic communication frameworks to enable multi‑agent orchestration. 5. Optimise code and deployment architectures to minimise Mean Time to Resolution (MTTR) and maximise ticket deflection rates. 6. Conduct security reviews aligned with OWASP Top 10 for LLMs, applying data‑masking and encryption best practices. 7. Prototype innovative automation solutions for high‑volume, repetitive IT tasks and present design patterns to the engineering community. 8. Mentor junior engineers, conduct code reviews and contribute to the AI Lab’s knowledge base. 9. Collaborate with product managers, data scientists and UX designers to translate business requirements into AI‑driven features. 10. Monitor production systems, troubleshoot issues, and continuously improve model performance and cost efficiency. Tech stack: Python, Node.js, AWS (Bedrock, Lambda, ECS/EKS), PostgreSQL with pgvector, Pinecone, AWS S3, REST/gRPC, SAP web services, JIRA/BMC Helix APIs, Model Context Protocol (MCP), OWASP security guidelines, Docker/Kubernetes, CI/CD pipelines. Growth path: Successful contributors can progress to Senior AI Engineer, Lead AI Architect, or AI Lab Manager, with opportunities to lead cross‑functional AI initiatives across the enterprise. Why join Enterprise? The company offers exposure to cutting‑edge generative AI technologies, a collaborative environment that values innovation, and a clear roadmap for career advancement. Employees benefit from continuous up‑skilling programs, mentorship from industry veterans, and the chance to work on projects that directly impact Fortune 500 clients worldwide.