Senior AI Engineer, Assistant Vice President

od 182k PLNod 182 004 PLN/ rok./ rok.UoPUmowa o pracę (brutto)

SeniorHybryda·KrakówFull-time·Umowa o pracę

#477356·Dodano 5 dni temu·0

Źródło: State Street

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Tech Stack / Keywords

Python LLMsRAGMLOpsLLMOpsDatabricks Snowflake Azure AWSvector search

Podsumowanie oferty

Develop and deliver production-grade AI solutions that support automation, insight generation, and scalable intelligence across enterprise platforms. The hands-on role focuses on Generative AI, large language models (LLMs), machine learning, and modern AI engineering frameworks.

Wymagania

Mandatory requirements:

Strong programming skills in Python.
Experience building production-grade AI/ML systems.
Experience with microservices and API-based architectures.
Hands-on experience with LLMs and prompt engineering, RAG pipelines and embeddings, and vector search and retrieval systems.
Experience building agent-based AI workflows.
Experience with platforms such as Databricks, Azure AI, or AWS AI services.
Knowledge of MLOps / LLMOps, including deployment and monitoring.
Ability to optimize systems for latency, scale, and cost.
Understanding of data engineering concepts and distributed systems.
Ability to integrate AI systems with enterprise data platforms and APIs.
Experience working in regulated or enterprise environments.
Ability to translate business needs into practical AI solutions.
Strong collaboration and communication skills.
B.S. degree in Computer Science, Engineering, Mathematics, Physics, or another technical course of study; an M.S. degree is strongly preferred.
Minimum 8–10 years of related experience, including 3+ years in AI/ML/Generative AI.

Nice to have:

Experience in financial services or capital markets.
Familiarity with Databricks or Snowflake.
Experience building AI copilots or document intelligence solutions.
Exposure to AI governance or model risk frameworks.

Obowiązki

AI Engineering & Development

Design, build, and deploy production AI and ML solutions.
Develop LLM-based applications, including prompt engineering and inference workflows.
Build RAG pipelines using structured and unstructured enterprise data.
Implement embeddings, semantic search, and vector-based retrieval.
Develop agent-based and multi-step AI workflows.

Production Delivery & Operations

Build and maintain AI services and APIs for enterprise use.
Implement MLOps / LLMOps practices, including model deployment, versioning, monitoring, evaluation, logging, and rollback strategies.
Optimize systems for performance, scalability, and cost efficiency.
Integrate AI solutions with Databricks, Snowflake, and cloud platforms (Azure / AWS).

Data & Integration

Ensure data readiness for AI use cases, including quality, access, and transformation.
Integrate AI solutions with enterprise data platforms and APIs.
Partner with data teams to support AI-driven pipelines and workflows.

Governance & Risk

Implement controls for data privacy, security, and model reliability.
Apply techniques for validation, explainability, and hallucination mitigation.
Align with enterprise standards for compliance and auditability.

Use Case Delivery

Translate business problems into deployable AI solutions.
Deliver use cases such as intelligent document processing, AI copilots for operations and analytics, and data-driven insights for markets and corporate functions.

Benefity

Additional holidays, including a birthday day off and days off on the 3rd and 5th work anniversaries.
Gold medical package for employees and their families, including partners and children.
Premium life insurance package and private pension plan.
Soft skills training, technical workshops, language classes, and development programs.
Discretionary annual performance-based awards.

Płatny urlop

Opieka zdrowotna

Ubezpieczenie

Szkolenia wewnętrzne

Kursy językowe

Premie

Inne informacje

The role requires working from the office at least three days per week.

State Street

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