Описание
The client is a global investment management company headquartered in London. It manages over $228 billion in assets for institutional investors, pension funds, wealth managers, and other sophisticated clients worldwide, specializing in quantitative investing, alternative investments, systematic trading strategies, and technology-driven asset management.
Задачи
•Design and build production backend services and APIs in .NET/C# and/or Python for internal applications and AI agents
•Build data access and integration layers connecting AI-enabled applications with enterprise data sources
•Develop agent-consumable APIs and tools for controlled enterprise data discovery, retrieval, and interpretation
•Build and enhance data catalogue and metadata capabilities
•Implement ingestion and transformation pipelines for structured and semi-structured data
•Build automated data-quality controls
•Implement provenance and traceability mechanisms
•Build entitlement-aware data services
•Develop semantic and analytical services for AI applications
•Integrate with existing AI and data platforms following architecture, security, governance, and operational standards
•Design solutions for large-scale enterprise and on-premise data estates
•Implement automated testing and quality gates
•Implement monitoring and observability for services and pipelines
•Work with AI engineers, data engineers, platform teams, architects, and business stakeholders to convert requirements into technical capabilities
•Participate in solution design, technical reviews, and architectural discussions
•Support production readiness and continuous improvement, including performance optimization, troubleshooting, and technical debt reduction
Требования
•5+ Years of production software engineering experience with strong hands-on expertise in .NET/C# and Python
•Strong experience designing and developing production APIs and backend services
•Experience with asynchronous processing and distributed systems
•Hands-on experience with data-intensive applications and data engineering
•Strong SQL skills and experience with relational databases and large enterprise datasets
•Experience designing data access and integration layers across heterogeneous enterprise sources
•Experience building metadata-driven services, catalogue integrations, or discovery capabilities
•Understanding of data modelling, metadata, data lineage, provenance, and data quality
•Experience implementing data validation and quality controls
•Experience designing secure and governed data access, including authentication, authorization, entitlements, and permission-aware APIs
•Strong understanding of clean architecture, SOLID principles, automated testing, CI/CD, code review, observability, and production support
•Experience with cloud and/or on-premise enterprise environments
•Comfortable using AI-assisted development tools and working with AI agents and LLM-based applications
•Understanding of tool/function calling, APIs, retrieval, and context management in LLM and agentic systems
•Ability to translate business and data requirements into scalable technical solutions
•Ability to work directly with architects, data engineers, platform engineers, and business stakeholders
•Fluent English
•Ability to operate independently within a client-facing, distributed engineering team
Nice to have: Experience with Snowflake, Databricks, SQL Server, PostgreSQL or similar enterprise data platforms, services consumed by AI agents, MCP servers or other agent/tool integration frameworks, data catalogues, semantic layers, data dictionaries, metadata management or data governance platforms, embeddings, vector search, semantic search or RAG, event-driven architectures, messaging platforms and background processing, fine-grained access control or entitlement models, financial markets, investment data, fund reporting or reference data, financial services or another regulated environment.
Условия
•Remote work is available from Bulgaria, Sofia
•No conditions specified
