Senior AI Engineer – Investment Technology

Location: New York, USA
Salary: $200,000-$250,000 base + discretionary bonus
Employment Type: Permanent
Sector: Hedge Fund/Alternative Investment Management

Build AI systems that influence how investment decisions are made.

What does AI engineering look like when your end users are some of the world’s most sophisticated investment professionals?

Cedar Technology is partnering with a leading global alternative investment management firm to recruit an experienced AI Engineer into its investment technology function.

This is an opportunity to work at the intersection of artificial intelligence, software engineering and financial markets, developing intelligent applications that enhance investment research, improve access to information and support complex decision-making.

Unlike roles focused primarily on proofs of concept, this position requires genuine software engineering expertise. You’ll be responsible for turning emerging AI capabilities into reliable, scalable applications that operate in a demanding, data-intensive environment.

You do not need previous hedge fund or financial services experience. We’re more interested in your ability to engineer sophisticated AI solutions and demonstrate the impact of what you’ve built.

The engineering challenge

You’ll collaborate with investment professionals, researchers and technology teams to identify opportunities where AI can deliver meaningful improvements to existing workflows.

Your responsibilities will include:

• Designing, developing and deploying AI-powered applications using modern large language models (LLMs).

• Building reliable, production-ready software using Python and modern engineering practices.

• Developing intelligent workflows that help investment professionals analyse, retrieve and interpret information.

• Evaluating emerging generative AI technologies and identifying commercially valuable applications.

• Integrating AI capabilities with existing datasets, applications and research tools.

• Improving application reliability, performance, scalability and maintainability.

• Collaborating directly with stakeholders to translate complex requirements into practical engineering solutions.

What we’re looking for

We’re interested in experienced software engineers who have moved beyond experimenting with AI and have successfully delivered intelligent applications into production.

Core experience:

• Approximately 5+ years of professional software engineering experience.

• Strong Python programming skills and a solid understanding of software architecture.

• Practical experience developing applications using LLMs and generative AI.

• Experience designing, building and maintaining production software.

• Strong understanding of APIs, data integration and scalable application development.

• Ability to evaluate technical trade-offs and solve complex engineering challenges.

• Excellent communication skills and confidence working directly with stakeholders.

Particularly relevant experience:

• Retrieval-augmented generation (RAG) and semantic search.

• AI agents, tool use and multi-step AI workflows.

• Model evaluation, monitoring and reliability.

• Modern cloud infrastructure and deployment practices.

• Developing applications involving complex or unstructured data.

You don’t need experience with every technology listed. We’re particularly interested in engineers who demonstrate strong fundamentals, technical curiosity and clear evidence of delivery.

Why consider this opportunity?

Sophisticated engineering challenges: Work on AI applications that must perform reliably in a technically demanding, data-rich environment.

Direct business impact: Develop solutions used by investment professionals, with the potential to influence how research is conducted and information is analysed.

Access to exceptional expertise: Collaborate with experienced engineers, quantitative researchers and investment specialists.

Real ownership: Contribute to the architecture, development and evolution of AI capabilities rather than simply integrating third-party tools.

Competitive compensation: Base salary of $200,000-$250,000, with additional discretionary bonus potential.

Why work with Cedar Technology?

At Cedar Technology, we specialise in Applied AI, Machine Learning, AI Engineering and the infrastructure required to operate intelligent systems at scale.

We understand that there’s a significant difference between building an impressive AI prototype and engineering a dependable application that creates measurable business value.

Our PROVEN assessment framework focuses on six areas:

• P – Production Experience: What have you actually delivered into production?

• R – Results Delivered: What measurable impact did your work create?

• O – Ownership: Which technical decisions and outcomes were genuinely yours?

• V – Validation of Experience: Can you demonstrate the depth of your expertise?

• E – Engineering Execution: How do you approach architecture, reliability and delivery?

• N – Needs Alignment: How does your experience match the challenges of the role?

Our aim is simple: connect exceptional engineers with organisations where their technical capability can make a meaningful difference and for you to get the opportunity of a lifetime.

Interested?

If you’re a strong software engineer with hands-on experience building production AI applications, we’d welcome a confidential conversation.

You don’t need a background in investment management. You do need the engineering capability, intellectual curiosity and ambition to solve complex technical problems.

Apply today or contact Cedar Technology, the specialist technology practice of Cedar Recruitment Limited, to discuss the opportunity in confidence.

Please note: Cedar Technology is acting as a recruitment agency in relation to this permanent appointment.

Tagged as: Agentic AI, AI Agents, AI Applications, AI Engineering, Artificial Intelligence, GenAI, Generative AI, Large Language Models, LLMs, Machine Learning, Model Evaluation, Production AI, Prompt Engineering, Python, R, Retrieval Augmented Generation, Software Engineering