Python & Java AI Developer

Python & Java AI Developer

Job Type: Full Time
Location: Toronto, ON
Work Model: Hybrid 4 Days Onsite

Primary Skills

Python & Java, Generative AI & Agentic AI, LLM/RAG & AI Engineering

Job Description

We are seeking an experienced Python & Java AI Developer to support an enterprise-wide Generative AI and Agentic AI initiative within a regulated banking environment. The successful candidate will combine strong Python and Java software engineering expertise with hands-on experience designing and implementing secure, scalable AI, Generative AI, and agentic solutions.

The role will support the complete AI solution lifecycle, from use-case discovery and prototyping through production implementation and support. The developer will collaborate closely with business, product, architecture, data, security, and engineering teams to deliver measurable business outcomes.

Key Responsibilities

• Design, develop, test, deploy, and support AI-enabled enterprise applications using Python and Java.
• Develop Generative AI solutions including conversational assistants, RAG pipelines, enterprise search, summarization, and workflow automation.
• Build agentic AI capabilities using tool/function calling, orchestration, guardrails, human-in-the-loop controls, and auditable execution flows.
• Integrate Large Language Models (LLMs), machine learning models, APIs, vector stores, enterprise data sources, and existing applications.
• Develop scalable REST APIs and microservices using modern Python and Java frameworks.
• Implement prompt engineering, document chunking, embeddings, retrieval, reranking, grounded response generation, and output validation.
• Design and implement evaluation frameworks covering accuracy, groundedness, safety, latency, reliability, and cost.
• Automate regression testing and evaluation of AI model behavior and application responses.
• Implement MLOps and LLMOps practices including version control, CI/CD, containerization, model and prompt versioning, monitoring, and incident support.
• Apply privacy, security, identity and access management, responsible AI, and model-risk controls appropriate for a regulated banking environment.
• Partner with business and technical stakeholders to identify use cases, assess feasibility, define acceptance criteria, and demonstrate prototypes.
• Transition successful AI solutions from proof-of-concept into production-ready enterprise applications.
• Perform code reviews, troubleshoot complex technical issues, and document architecture and technical decisions.
• Mentor engineering team members and contribute to development standards and best practices.

Required Skills & Experience

• Strong hands-on experience with Python and Java development.
• Experience building enterprise-grade applications, APIs, and microservices.
• Hands-on experience with Generative AI and Large Language Models (LLMs).
• Strong understanding of Retrieval-Augmented Generation (RAG) architectures.
• Experience with prompt engineering, embeddings, vector search, retrieval, reranking, and response validation.
• Experience designing or implementing Agentic AI solutions and orchestration workflows.
• Experience integrating AI/ML models with enterprise applications and data sources.
• Strong understanding of REST APIs, microservices, CI/CD, and software engineering best practices.
• Knowledge of AI evaluation, testing, monitoring, reliability, and cost optimization.
• Understanding of security, privacy, responsible AI, and governance requirements.

Preferred Skills

• Experience with Azure AI Services, Azure OpenAI, Azure AI Search, or comparable cloud AI platforms.
• Experience with LangChain, Semantic Kernel, LlamaIndex, PyTorch, TensorFlow, or scikit-learn.
• Knowledge of agentic AI patterns, Model Context Protocol (MCP), and multi-agent orchestration.
• Experience with enterprise knowledge platforms and vector databases.
• Experience implementing AI governance, responsible AI controls, privacy safeguards, content safety, and model-risk documentation.
• Experience with GitHub Copilot or other AI-assisted development tools.
• Experience with Docker, Kubernetes, and cloud-native application development is an advantage.

Banking & Regulatory Experience

• Prior experience in the Banking or Financial Services domain is preferred.
• Understanding of security, audit, compliance, privacy, and data-governance requirements in regulated environments.
• Experience developing enterprise solutions that meet organizational security and risk-management standards.

MLOps & LLMOps

• Implement model and prompt versioning and lifecycle management.
• Build CI/CD pipelines for AI-enabled applications.
• Implement monitoring for model performance, application reliability, latency, safety, and cost.
• Support production incidents and continuous improvement of AI solutions.
• Establish automated evaluation and regression-testing processes for AI behavior.

Collaboration & Delivery

• Work closely with business stakeholders, Product Owners, Architects, Data Scientists, Security teams, and Engineering teams.
• Participate in Agile ceremonies, sprint planning, code reviews, demonstrations, and retrospectives.
• Translate business requirements into scalable AI and software solutions.
• Clearly communicate technical concepts and AI capabilities to both technical and non-technical stakeholders.