Senior Data Engineer

BP INCORPORATE INTERNATIONAL.

5 - 10 years

7 - 12 Lacs

pune

Posted:5 hours ago| Platform:

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Skills Required

automation software design business analysis project management information security configuration management data structures risk management analytics python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Design, develop, and maintain production-grade AI applications and services using modern software engineering practices (CI/CD, testing, observability, cloud-native design).
Define and implement foundational platforms and tools (e.g., conversational bots, AI-powered search, unstructured data processing, GenBI) that are reusable and scalable across the enterprise.
Participate in cross functional team initiatives embedded projects with business stakeholders to rapidly build and deploy AI solutions that solve high-priority business problems.
Evaluate and integrate existing AI tools, frameworks, and APIs (e.g., LLMs, vector DBs, retrieval-augmented generation, AI agents) into robust applications.
Champion automation in workflows from data management ingestion and preprocessing to evaluation, to model integration and deployment.
Collaborate with data scientists, product managers, and other engineers to ensure end-to-end delivery and reliability of AI products.
Stay current with emerging AI technologies, but prioritize practical application and delivery over experimental research.
Contribute to the internal knowledge base, tooling libraries, and documentation to scale AI engineering best practices across the organization.

Job Qualifications

Required:

5+ years of professional software engineering experience; ability to independently design and ship complex systems in production.
Strong programming skills in Python (preferred), Java, or similar languages, with experience in developing microservices, APIs, and backend systems.
Strong problem-solving skills and the ability to balance engineering rigor with delivery speed
Solid understanding of software architecture, cloud infrastructure (AWS, Azure, or GCP), and modern DevOps practices.
Experience integrating machine learning models into production systems (e.g., LLMs via APIs, fine-tuning, RAG patterns, embeddings, agents and crew of agents etc.).
Ability to move quickly while maintaining code quality, test coverage, and operational excellence.

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