Python & Java AI Developer
Acestack
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 DescriptionWe 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.
- 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.
- 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.
- 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.
- 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.
- 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.
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