Job Purpose
As a Senior Software Engineer (AI), you will play a pivotal role in driving the adoption of Artificial Intelligence and Machine Learning across our product and engineering ecosystem. You will lead the design, development, and deployment of enterprise-grade AI solutions that enhance customer experience, improve engineering productivity, and enable intelligent data management.
Working closely with Product Managers, Architects, Data Engineers, and Software Engineers, you will help shape the AI strategy for our modern enterprise data platforms while driving innovation using the latest advancements in Generative AI, Agentic AI, and cloud-native technologies.
Job Responsibilities
- Design, develop, and deploy AI-powered applications by leveraging Large Language Models (LLMs), Agentic AI, and modern AI frameworks.
- Build/leverage enterprise-grade AI assistants and copilots to accelerate software development, testing, documentation, customer support, and operational workflows.
- Design and implement Retrieval Augmented Generation (RAG), semantic search, vector search, and enterprise knowledge solutions.
- Develop AI agents and orchestrate multi-agent workflows using modern AI frameworks and Model Context Protocol (MCP).
- Build scalable AI services and APIs that integrate seamlessly with enterprise applications and data platforms.
- Evaluate emerging AI models, frameworks, and technologies, providing technical recommendations and proof-of-concepts.
- Collaborate with cross-functional teams to identify high-value AI use cases and drive successful implementation.
- Establish best practices for prompt engineering, LLM evaluation, governance, security, and responsible AI adoption.
Job Requirements
- Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related discipline.
- 6+ years of professional software engineering experience, including hands-on experience designing and delivering enterprise-grade AI solutions.
- Proven expertise in Generative AI, LLM integration, RAG, AI Agents, cloud-native application development, and modern data platforms.
- Experience with enterprise data management platforms, Databricks, Spark, AWS, and distributed systems will be a significant advantage.
Artificial Intelligence & Machine Learning
- Hands-on experience developing production-grade AI solutions using leading LLMs such as OpenAI, Claude, Gemini, Llama, or similar models.
- Strong experience with Prompt Engineering, Retrieval Augmented Generation (RAG), AI Agents, embeddings,semantic search, and vector search.
- Experience implementing enterprise AI solutions using frameworks such as LangChain, LangGraph, LlamaIndex, Hugging Face, or equivalent.
- Experience building AI agents using Model Context Protocol (MCP) and integrating external tools and enterprise systems.
- Knowledge of AI evaluation techniques, guardrails, observability, and LLMOps best practices.
Software Engineering
- Strong programming experience in Python with proficiency in SQL, REST APIs, and either Java or .NET.
- Experience developing scalable, cloud-native microservices and enterprise applications.
- Strong understanding of software design principles, APIs, testing strategies, and system integration.
Data & Cloud Technologies
- Experience working with enterprise data platforms such as Databricks, Snowflake, Apache Spark, Delta Lake, Apache Iceberg, and AWS.
- Experience with cloud storage technologies including Amazon S3 and vector databases such as Pinecone, Chroma, Milvus, or similar.
- Good understanding of modern data lakehouse architectures and enterprise data management principles.
- Experience designing and optimizing ETL/ELT pipelines using technologies such as Python, SQL, Spark, Airflow, or dbt is desirable.
Additional Preferred Qualifications
- Experience building and operating large-scale distributed systems in cloud environments.
- Experience with DevOps practices, CI/CD pipelines, Infrastructure as Code, and observability platforms.
- Strong scripting and automation skills using Python, Bash, or PowerShell, with exposure to AI-assisted automation.
- Experience designing scalable technical architectures and communicating complex technical concepts to both technical and non-technical stakeholders.
- AWS, Databricks, Azure AI, or equivalent cloud certifications are advantageous.
- Experience in Enterprise Data Management, Master Data Management (MDM), Financial Services, or Capital Markets is highly desirable.
Soft Skills
- Strong analytical and problem-solving abilities with a passion for AI-driven innovation.
- Excellent communication, stakeholder management, and cross-functional collaboration skills.
- Demonstrated technical leadership and the ability to mentor engineers and drive engineering best practices.
- Ability to manage multiple priorities and deliver high-quality solutions in a fast-paced environment.
- Curiosity, continuous learning mindset, and enthusiasm for emerging AI technologies.
Equal Opportunities Statement
At Gresham, we are committed to building a diverse and inclusive workforce that reflects the communities we serve. We actively encourage applications from individuals of all backgrounds and are dedicated to providing a workplace where everyone feels valued, respected and supported.
We make employment decisions based on merit, skills and potential, and do not discriminate based on any protected characteristic. We are also committed to making reasonable adjustments throughout the recruitment process and employment lifecycle.
Company Summary
Gresham is a global financial services technology company specialising in enterprise data automation. We help financial institutions ensure that their operational, regulatory and management data is complete, accurate, timely and fully auditable — particularly within complex environments where data is distributed across multiple systems.
Our solutions automate data controls, reconciliations, workflows and exception management, enabling clients to reduce operational risk, strengthen data governance and enhance confidence in reporting across highly regulated environments. Serving both buy-side and sell-side organisations worldwide, Gresham partners with clients to deliver trusted, transparent and resilient data operations.
