.net developer regulated financial firms

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.

• 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.

• 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.

Remote work is available from Bulgaria, Sofia;
No conditions specified.