Job Description Summary

Job Description

Core Responsibilities:

• Design and Develop: AI-powered applications integrating machine learning and generative models into enterprise-grade software products and internal tools. Owning the full software development lifecycle (SDLC) including unit integration and end-to-end testing.

• Frontend: Developing modern intuitive interfaces for AI applications (React/ TypeScript or equivalent) with a strong focus on usability accessibility and AI explainability.

• Backend: Implementing scalable and secure back-end services (FastAPI Flask or ) to expose AI capabilities (LLMs RAG pipelines AI agents) through standardized APIs.

• Translating data science prototypes and GenAI models (LLMs diffusion models transformers) into scalable applications or services with intuitive user interfaces and reliable back-end infrastructure.

• Collaborating with Insight Leaders and business stakeholders on requirements gathering project documentation and development planning.

• Partnering with MLOps and GenAIOps teams to deploy monitor and continuously improve AI applications within standardized CI/CD pipelines.

• Designing and implementing integrations using REST GraphQL and gRPC; work with cloud-based AI APIs (Azure AWS GCP) and enterprise data sources.

• Integrating cloud-native AI services (AWS Bedrock Azure OpenAI) and open-source frameworks (LangChain LangGraph) into enterprise environments.

• Monitoring application performance and user adoption iterating on models and workflows to enhance usability and business impact.

• Optimizing application performance infrastructure efficiency and LLM utilization.

• Documenting architectures APIs and deployment processes to ensure transparency reusability and maintainability.

Requirements

• Education: Masters or PhD degree (or equivalent experience) in Computer Science Software Engineering Artificial Intelligence or related STEM field.

• Experience: hands-on experience developing and deploying AI-powered or data-driven applications in enterprise environments.

• Advanced proficiency in Python plus strong working knowledge of TypeScript/JavaScript and at least one modern web framework (React FastAPI Flask).

• Proven track record implementing end-to-end AI systems integrating ML/LLM models into scalable microservices or enterprise applications.

• Strong experience in ML/GenAI frameworks (TensorFlow PyTorch LangChain AutoGen Semantic Kernel) and cloud-native AI platforms (AWS Bedrock Azure OpenAI).

• Working knowledge of cloud environments (AWS Azure or GCP) and containerization tools (Docker).

• Deep experience with Docker Kubernetes and CI/CD automation for AI workloads.

• Demonstrated experience with RAG pipelines vector databases and document retrieval frameworks.

• Solid understanding of LLMOps / GenAIOps integration patterns model evaluation and prompt optimization workflows.

• Strong collaboration skills and the ability to communicate effectively within cross-functional teams.

• Ability to mentor junior engineers perform code reviews and contribute to architectural decisions.

• Strong problem-solving debugging and analytical skills with clear and persuasive communication to technical and business audiences.

#LI-MT1

#LI-Hybrid

Pay Range

Placement within this range depends on:

• Relevant skills and qualifications

• Prior job-related experience

• Internal equity considerations (alignment with colleagues in similar roles) e.t.c.

We review pay ranges regularly to ensure they remain competitive with the external market and align with our internal equity considerations.

Benefits & Rewards

In addition to base salary our employees have access to a comprehensive package of benefits and allowances which may include:

• Health & wellness coverage

• Retirement and or savings plans

• Allowances or benefits to support role requirements (e.g. mobility transport or role-specific needs such as a company car or allowance where applicable)

• Work-life balance support (e.g. flexible working leave programs)

• Recognition and incentive programs aligned with performance and company success

The exact benefits package depends on the role location and employment terms as specified in the Colleague Value Proposition document that will be shared prior to the interview or at the offer discussion stage.

• Performance Bonus: Details to be shared during offer discussions

Additional Information

Relocation Assistance Provided: Yes