Senior AI Developer – Investments & Agentic Platform
About Invesco
As one of the world's leading independent global investment firms, Invesco is dedicated to rethinking possibilities for our clients. By delivering the combined power of our distinctive investment management capabilities, we provide a wide range of investment strategies and vehicles to our clients around the world. If you're looking for challenging work, intelligent colleagues, and exposure across a global footprint, come explore your potential at Invesco.
What's in it for you?
Our people are at the ver y core of our success. Invesco employees get more out of life through our comprehensive compensation and benefit offerings including:
- Flexible paid time off
- Hybrid work schedule
- 401(K) matching of 100% up to the first 6% with a discretionary supplemental contribution
- Health & wellbeing benefits
- Parental Leave benefits
- Employee stock purchase plan
Job Description
About the Role
AI Platform Development
- Build reusable AI platform components that can be leveraged across multiple business capabilities.
- Integrate AI solutions with enterprise data platforms, model platforms, and business applications.
- Support governance, security, observability, and operational requirements for production AI solutions.
- Contribute to the development of a scalable and maintainable AI ecosystem that supports both experimentation and enterprise adoption.
Semantic Layer Development
- Lead the design and implementation of a common semantic layer supporting Investments and Distribution use cases.
- Define semantic models, taxonomies, metadata structures, and business definitions that improve data accessibility and consistency.
- Work with data, engineering, and business teams to ensure a governed and reusable data foundation for AI solutions.
- Support natural language access to investment data through semantic and AI services.
AI Agent Development
- Design and develop AI agents that support investment research, portfolio management, risk analysis, performance analytics, product intelligence, and distribution workflows.
- Build reusable agent frameworks, orchestration patterns, and integration approaches.
- Develop multi-step AI workflows that combine structured and unstructured data sources.
- Establish approaches for agent evaluation, testing, observability, and continuous improvement.
AI Innovation & Technical Excellence
- Stay current with emerging AI technologies, frameworks, and industry trends, identifying opportunities to apply them within Investments Technology.
- Evaluate new tools and platforms through proof-of-concepts and practical experimentation.
- Contribute to AI architecture decisions and implementation standards.
- Share knowledge with development teams through mentoring, demonstrations, technical workshops, and documentation.
- Promote engineering best practices for building scalable, secure, and maintainable AI solutions.
Spec-Driven Development & AI Engineering
- Help introduce and scale Spec-Driven Development practices within Investments Technology.
- Leverage AI-assisted development tools to improve productivity and software quality.
- Contribute to standards for specification creation, automated testing, and AI-assisted delivery workflows.
- Develop reusable templates, reference implementations, and engineering patterns that accelerate solution delivery.
Requirements of the Role
- Strong software engineering experience with demonstrated delivery of enterprise applications.
- Hands-on experience designing and developing Generative AI, agentic AI, or machine learning solutions.
- Experience working with modern AI frameworks, orchestration platforms, and large language models.
- Strong understanding of enterprise application architecture and integration patterns.
- Experience working directly with business stakeholders to translate requirements into technical solutions.
- Excellent problem-solving, communication, and collaboration skills.
- Passion for continuous learning and applying emerging technologies.
Preferred Experience
- Experience within asset management, wealth management, investment management, research, trading, risk, or financial services.
- Experience developing semantic models, knowledge layers, metadata frameworks, or business taxonomies.
- Experience building enterprise AI agents and AI-enabled workflow solutions.
- Experience implementing AI governance, evaluation, and observability capabilities.
- Experience operating across Snowflake, AWS, and Microsoft AI ecosystems.
Enterprise AI Platforms
- Snowflake Cortex, Analyst, Search
- Snowflake Cortex Code
- AWS Bedrock, AgentCore, etc.
- Azure Agent Foundry
- Microsoft Copilot Studio
- Anthropic Claude
Agentic AI
- LangGraph
- LangChain
- Strands
- AutoGen
- CrewAI
- Model Context Protocol (MCP)
- Multi-Agent Systems
- Agent Orchestration Frameworks
Retrieval & Knowledge Systems
- Retrieval-Augmented Generation (RAG)
- GraphRAG
- Enterprise Search
- Semantic Search
- Knowledge Graphs
- Vector Search and Embeddings
- Hybrid Retrieval Architectures
Semantic Layer & Data Intelligence
- Semantic Modeling
- Business Taxonomies
- Metadata Management
- Ontology Design
- Data Catalogs
- Knowledge Representation
- AI Data Governance
AI Engineering & Operations
- Spec-Driven Development (SDD)
- AI-Assisted Development
- AI Coding Agents
- LLM Evaluation Frameworks
- Prompt Engineering
- Context Engineering
- AI Observability
- AI Guardrails and Safety Controls
- Human-in-the-Loop Workflows
- LLMOps
Full Time / Part Time
Worker Type
Job Exempt (Yes / No)
Workplace Model
Not included in the source posting: benefits.
Skills
Who can apply
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