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Added 28 mins ago
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AceStack

Python & Java AI Developer / Toronto, ON (Hybrid) - FTE

Toronto, ON, Canada

Job type: Full-time
Apply by: Oct 30, 2026
Experience: 8+ years of software engineering experience, with strong hands-on development in Python and Java.
Posting language: English
Posted: Sep 30, 2026

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Original job description

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

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More about this job

Responsibilities

Design, build, test, deploy, and support secure, production-ready AI applications using Python and Java, including RAG, conversational assistants, enterprise search, and agentic workflows. Integrate models, APIs, vector databases, and enterprise data while implementing evaluation, testing, monitoring, governance, and security controls; collaborate with stakeholders and mentor engineers.

Requirements

Requires 8+ years of software engineering experience with strong hands-on Python and Java development, plus proven experience delivering enterprise Generative AI and LLM applications. Candidates should have expertise in RAG, agentic AI, APIs and microservices, cloud-native engineering, CI/CD, testing, production support, and enterprise security, and be effective cross-functional collaborators.

Skills

Python
Java
Generative AI
Agentic AI
Large Language Models
Retrieval-Augmented Generation
Prompt Engineering
Embeddings
Vector Search
REST APIs
Microservices
Azure OpenAI
CI/CD
Docker
LLMOps
AI Security

Visa sponsorship

Not detected in the job text

Keywords

Python
Java
Generative AI
Agentic AI
Large Language Models
Retrieval-Augmented Generation
Prompt Engineering
Embeddings
Vector Databases
Vector Search
LangChain
Semantic Kernel
LlamaIndex
Azure OpenAI
Azure AI Search
REST APIs
Microservices
Docker
CI/CD
Git
LLMOps
MLOps
AI Evaluation
Observability
Guardrails
Model Context Protocol
Responsible AI
Data Governance
Banking
Financial Services

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