Job Title: Python & Java AI Developer
Location: Toronto, ON
Work Model: Hybrid – 4 Days Onsite
Role Type: Senior AI Software Engineer
Focus: Python, Java, Generative AI & Agentic AI
Role Overview
We are seeking a Senior AI Software Engineer with strong hands-on experience in Python, Java, Generative AI, and Agentic AI to support an enterprise AI initiative within a regulated banking environment.
The successful candidate will be responsible for taking AI use cases from discovery and prototyping through production implementation, working closely with business, product, architecture, data, security, and engineering teams.
The role requires a strong software engineering foundation combined with practical experience designing and delivering secure, scalable, production-ready AI solutions.
Key Responsibilities
- Design, develop, test, deploy, and support enterprise AI applications using Python and Java.
- Build Generative AI solutions, including conversational assistants, RAG applications, enterprise search, summarization, and intelligent workflow automation.
- Develop Agentic AI solutions using tool/function calling, orchestration, guardrails, human-in-the-loop controls, and auditable execution workflows.
- Integrate LLMs, ML models, REST APIs, vector databases, 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 generation, and output validation.
- Design and implement AI evaluation frameworks covering accuracy, groundedness, safety, latency, reliability, and cost.
- Develop automated regression and testing frameworks for AI/LLM behavior and application functionality.
- Apply MLOps and LLMOps practices, including CI/CD, version control, containerization, model/prompt versioning, observability, monitoring, and production support.
- Implement appropriate security, privacy, IAM, responsible AI, data governance, and model-risk controls for enterprise AI solutions.
- Collaborate with business and technical stakeholders to identify use cases, assess feasibility, define acceptance criteria, build prototypes, and transition solutions into production.
- Participate in architecture and design discussions and contribute to technical solution decisions.
- Perform code reviews, troubleshoot complex production issues, and ensure engineering best practices.
- Create and maintain technical documentation, architecture decisions, and operational runbooks.
- Mentor junior and intermediate engineers and contribute to continuous improvement of AI engineering practices.
Required Skills & Experience
- 8+ years of software engineering experience, with strong hands-on development in Python and Java.
- Proven experience building and deploying Generative AI / LLM-based applications in enterprise environments.
- Strong experience with RAG, embeddings, vector search, prompt engineering, document processing, retrieval, and response grounding.
- Hands-on experience developing Agentic AI applications, including tool/function calling, orchestration, workflows, guardrails, and human-in-the-loop patterns.
- Strong experience developing REST APIs, microservices, and cloud-native applications.
- Experience integrating LLMs, AI/ML models, APIs, enterprise data platforms, and third-party services.
- Experience with CI/CD, Git, Docker/containerization, automated testing, monitoring, and production support.
- Strong understanding of AI security, privacy, responsible AI, data governance, and enterprise application security.
- Experience working with cross-functional teams in Agile environments.
- Strong communication, problem-solving, and technical leadership skills.
Preferred Qualifications
- Experience with Azure AI, Azure OpenAI, Azure AI Search, or comparable cloud AI platforms.
- Experience with LangChain, Semantic Kernel, LlamaIndex, PyTorch, TensorFlow, or scikit-learn.
- Knowledge of Model Context Protocol (MCP), multi-agent architectures, agent orchestration, and enterprise knowledge platforms.
- Experience with AI evaluation, observability, LLMOps, model governance, and AI safety controls.
- Experience implementing privacy safeguards, content safety controls, and model-risk documentation.
- Previous experience in banking or financial services, particularly within regulated enterprise environments.
- Familiarity with security, audit, compliance, risk management, and data-governance requirements in financial institutions.
- Experience using GitHub Copilot or other AI-assisted software development tools.
Core Technology Stack
- Programming: Python, Java
- AI/GenAI: LLMs, Generative AI, RAG, Agentic AI, Prompt Engineering, Embeddings, Vector Search
- AI Frameworks: LangChain, Semantic Kernel, LlamaIndex, PyTorch, TensorFlow, scikit-learn
- Cloud: Azure, Azure OpenAI, Azure AI Search
- Engineering: REST APIs, Microservices, Docker, CI/CD, Git
- AI Engineering: LLMOps, MLOps, Evaluation, Observability, Guardrails
- Enterprise: Security, IAM, Privacy, Responsible AI, Data Governance, Model Risk
- Domain: Banking / Financial Services preferred
