Data Engineer+GenAI Engineer (Forward developer)(5+ yrs)

Job Description: Forward Deployed Engineer (FDE)Experience: 5+ Years

Location: Remote || Contract

Practice: Data & AI – Tata Elxsi

Job SummaryWe are looking for an experienced Forward Deployed Engineer (FDE) who combines strong software engineering, data engineering, Generative AI, and cloud deployment expertise. The ideal candidate will work directly with customers and internal engineering teams to understand business challenges, design technical solutions, and build and deploy scalable, production-ready applications.

The role requires hands-on experience in Python, SQL, APIs, cloud platforms, data pipelines, and AI/LLM-based applications, along with strong customer-facing communication and problem-solving skills.

Key Responsibilities

• Engage with customer stakeholders to understand business requirements, technical challenges, and desired outcomes.
• Design, develop, and deploy end-to-end solutions, including prototypes, MVPs, and production-grade applications.
• Build data pipelines, ETL/ELT workflows, APIs, and enterprise system integrations.
• Develop and integrate GenAI applications, including RAG-based solutions, AI agents, copilots, and knowledge management systems.
• Integrate enterprise data sources, databases, third-party APIs, and business applications.
• Deploy and manage applications on AWS, Azure, or GCP using cloud-native technologies.
• Optimize application performance, scalability, reliability, security, and cost.
• Collaborate with data engineers, AI engineers, product teams, and customer IT teams to deliver business outcomes.
• Troubleshoot production issues and support continuous improvement.
• Follow software engineering best practices, including version control, CI/CD, testing, and code reviews.Required Technical Skills1. Programming & Backend Development
• Strong hands-on experience with Python and SQL.
• Experience with REST APIs, backend development, and system integrations.
• Familiarity with Java, Scala, or Node.js is an advantage.
• Understanding of microservices architecture, Git, testing, and CI/CD.2. Data Engineering
• Experience building ETL/ELT pipelines and data integration workflows.
• Knowledge of data modelling, data warehousing, and data lakehouse architecture.
• Hands-on experience with PySpark, Apache Spark, Databricks, or equivalent data platforms.
• Ability to connect enterprise data sources to analytics and AI applications.3. Generative AI & Agentic AI
• Experience building applications using LLMs and Generative AI.
• Knowledge of Retrieval-Augmented Generation (RAG), embeddings, and vector databases.
• Hands-on experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent.
• Understanding of prompt engineering, AI agents, and LLM API integration.
• Ability to integrate AI-powered solutions with enterprise applications and data platforms.4. Cloud & Deployment
• Hands-on experience with at least one cloud platform: AWS, Azure, or GCP.
• Knowledge of Docker, Kubernetes, and cloud-native application deployment.
• Understanding of CI/CD pipelines, infrastructure automation, and production monitoring.
• Experience deploying, securing, and scaling production-grade applications.Customer-Facing & Consulting Skills
• Ability to translate business requirements into technical designs and implementation plans.
• Strong communication, analytical, debugging, and problem-solving skills.
• Experience collaborating directly with customers and managing technical stakeholders.
• Ability to work independently in a fast-paced, ambiguous environment.
• Strong ownership of solution delivery, customer satisfaction, and business outcomes.Preferred Qualifications
• Experience with Snowflake, MongoDB, Red Hat OpenShift, or enterprise data platforms.
• Knowledge of MLOps, LLMOps, and production AI monitoring.
• Experience integrating enterprise platforms such as SAP, Salesforce, ServiceNow, or Oracle.
• Exposure to industries such as automotive, healthcare, telecom, manufacturing, transportation, or energy.
• Experience developing reusable frameworks, accelerators, or enterprise AI solutions.EducationBachelor’s or Master’s degree in Computer Science, Engineering, Data Science, AI, or a related discipline.

Ideal Candidate ProfileCandidates with any of the following backgrounds are encouraged to apply:

• Data Engineer + GenAI Engineer: Python, SQL, PySpark, Databricks, ETL/ELT, cloud, RAG, and LLMs.
• GenAI Engineer + Backend Engineer: Python, FastAPI, REST APIs, LangChain/LangGraph, RAG, vector databases, Docker, and cloud.
• Cloud Solutions Engineer + AI/Data Engineer: AWS/Azure/GCP, Python, APIs, Kubernetes, CI/CD, cloud data services, and production AI deployment.Important: Candidates must demonstrate strong hands-on engineering capabilities, practical solution delivery experience, and the ability to work directly with customers. Purely theoretical AI/ML knowledge or candidates with only traditional data engineering experience and no software development or solution implementation exposure may not be suitable.