Senior.NET engineer/Python engineer

About the Position

We're seeking a Senior.NET engineer/Python engineer with strong data-engineering skills to join our global investment management company in a remote role.

Responsibilities

• Design and build production backend services and APIs in.NET/C# and/or Python that expose enterprise data and capabilities to internal applications and AI agents.
• Build the data access and integration layer connecting AI-enabled applications with databases, reports, analytical platforms, file systems, and other enterprise data sources.
• Develop agent-consumable APIs and tools that allow AI agents to discover, retrieve, and interpret enterprise data in a controlled and reliable way.
• Build and enhance data catalogue and metadata capabilities, enabling datasets, reports, fields, and other data assets to be discovered through consistent APIs and semantic metadata.
• Implement data ingestion and transformation pipelines for structured and semi-structured sources, including validation, normalization, enrichment, and metadata extraction.
• Build automated data-quality controls covering completeness, freshness, duplication, schema consistency, missing data, and other issues that could affect downstream AI applications.
• Implement provenance and traceability mechanisms, ensuring data returned to applications and AI agents can be traced back to its authoritative source.
• Build entitlement-aware data services, ensuring users and AI agents can access only the datasets and information they are authorized to consume.
• Develop semantic and analytical services that help AI applications understand relationships between datasets, business terminology, metadata, and analytical information.
• Integrate with the client’s existing AI and data platforms, following established architecture, security, governance, and operational standards.
• Design solutions for large-scale enterprise and on-premise data estates, considering performance, scalability, resilience, and maintainability.
• Implement automated testing and quality gates, including unit, integration, API, and regression testing for production services and data pipelines.
• Implement monitoring and observability for services and pipelines, including logging, metrics, error handling, and operational dashboards.
• Work closely with AI engineers, data engineers, platform teams, architects, and business stakeholders to convert business requirements into robust technical capabilities.
• Participate in solution design, technical reviews, and architectural discussions, identifying opportunities to simplify integrations and create reusable platform capabilities.
• Support production readiness and continuous improvement of services, including performance optimization, troubleshooting, and technical debt reduction.

Requirements

• 5+ years of production software engineering experience with strong hands-on expertise in.NET/C# and Python, building enterprise-grade backend services, APIs, and data-processing solutions.
• Strong experience designing and developing production APIs and backend services, including REST APIs, service integrations, asynchronous processing, and distributed systems.
• Hands-on experience with data-intensive applications and data engineering, including ingestion, transformation, validation, and processing of structured and semi-structured data.
• Strong SQL skills and practical experience working with relational databases and large enterprise datasets.
• Experience designing and implementing data access and integration layers across heterogeneous enterprise sources such as databases, APIs, file systems, data warehouses, and analytical platforms.
• Experience building metadata-driven services, catalogue integrations, or discovery capabilities that allow applications to find and interpret datasets, reports, fields, and other enterprise data assets.
• Understanding of data modelling, metadata, data lineage, provenance, and data quality concepts.
• Experience implementing data validation and quality controls, including completeness, freshness, schema validation, duplication, and consistency checks.
• Experience designing secure and governed data access, including authentication, authorization, entitlements, and permission-aware APIs.
• Strong understanding of software engineering best practices: clean architecture, SOLID principles, automated testing, CI/CD, code review, observability, and production support.
• Experience working with cloud and/or on-premise enterprise environments and integrating solutions with existing platforms rather than creating isolated services.
• Comfortable using AI-assisted development tools and working in an environment where AI agents and LLM-based applications consume the services being built.
• Understanding of how LLM/agentic systems interact with enterprise data and tools, including tool/function calling, APIs, retrieval, and context management.
• Ability to translate business and data requirements into scalable technical solutions and work directly with architects, data engineers, platform engineers, and business stakeholders.
• Fluent English and 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.
• Experience building services consumed by AI agents, MCP servers, or other agent/tool integration frameworks.
• Experience with data catalogues, semantic layers, data dictionaries, metadata management, or data governance platforms.
• Knowledge of embeddings, vector search, semantic search, or retrieval-augmented generation (RAG).
• Experience with event-driven architectures, messaging platforms, and background processing.
• Experience implementing fine-grained access control or entitlement models for enterprise data.
• Knowledge of financial markets, investment data, fund reporting, or reference data.
• Previous experience in financial services or another regulated environment.

We Offer

• Opportunity to work with a leading global investment management company.
• Remote work options.
• Collaborative and inclusive work environment.
• Professional growth and development opportunities.
• Competitive compensation package.

About the Company

At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth.

We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law.

We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.