3 дня назад
Lead Data & AI Engineer
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Lead Data & AI Engineer (GenAI/Data Platforms): Designing and scaling enterprise AI/GenAI applications, RAG solutions, intelligent agents, and workflow automation on governed data platforms with an accent on data lakes, lakehouses, APIs, and production-ready architectures. Focus on building reusable AI frameworks, integrating enterprise systems, and implementing evaluation, observability, security, and performance capabilities.
Location: Pune, India
Company
supports enterprise AI initiatives within its CIO organization.
What you will do
- Define and execute an enterprise AI strategy across applications, data platforms, and workflows.
- Design, develop, and deploy AI/GenAI applications, RAG solutions, intelligent agents, and workflow automation.
- Build scalable AI capabilities on structured, unstructured, and real-time enterprise data using data lake, lakehouse, and cloud data platforms.
- Architect backend services, APIs, integrations, and orchestration frameworks using LLMs, model APIs, and enterprise systems.
- Define AI governance, evaluation, observability, security, reliability, and performance frameworks.
- Collaborate with business and enterprise application teams to prototype and productionize high-impact AI use cases.
Requirements
- 7–12+ years of experience in software engineering, AI/ML, or GenAI application development.
- Experience implementing AI/ML or GenAI solutions on platforms such as Snowflake, Databricks, OCI, data lakes, or lakehouses.
- Strong understanding of enterprise data architecture, data pipelines, semantic layers, governance, and AI-ready data foundations.
- Strong expertise in Python, backend development, APIs, system integration, and workflow orchestration.
- Hands-on experience with RAG, LLMs, prompt engineering, tool and agent calling, AI evaluation, and observability.
- BE/B.Tech/MCA, preferably in computer science, information technology, or a related field.
Nice to have
- Experience with vector databases, embeddings, semantic search, and advanced RAG architectures.
- Knowledge of SQL, data engineering, and data pipelines.
- Experience with data quality, lineage, security, compliance, intelligent agents, automation platforms, or AI governance frameworks.
- Experience building reusable AI frameworks, accelerators, or enterprise AI platforms.
Culture & Benefits
- Innovation and teamwork are emphasized.
- Internal career growth is supported.
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