Assistant Python Jobs in Brampton, ON (NOW HIRING)

We are seeking a strong Python developer on a 1 -year fixed term role, with practical experience building applications that leverage large language models (LLMs). The ideal candidate has deep expertise in Python software engineering, APIs, data structures, and testing, and has contributed to at least one production or pilot use case involving LLMs (e.g., retrieval-augmented generation, summarization, classification, or code assistants). You will design, build, and optimize backend services and ML/LLM integrations with a focus on reliability, security, and measurable business impact.

• Design, develop, and maintain Python services, libraries, and APIs for data processing and application backends.
• Build and integrate LLM-driven features (prompting, context construction, chaining/orchestration, evaluation).
• Implement retrieval-augmented generation (RAG) pipelines, including document ingestion, chunking, embeddings, and vector search.
• Develop robust unit/integration tests; contribute to CI/CD pipelines and observability (logging, metrics, tracing).
• Optimize performance and cost of LLM workloads (token usage, latency, caching, batching, model selection).
• Ensure data privacy and security best practices, including PII handling, guardrails, and governance.
• Collaborate cross-functionally with product managers, data engineers, designers, and security to ship production-quality features.
• Document designs, decisions, and operational runbooks; mentor peers and review code.
• Monitor and troubleshoot production issues; drive continuous improvement and post-incident learnings.

This is your opportunity to work in Operate at Deloitte. Operate services harness the latest technologies, talent, and capabilities from all over the world to deliver ongoing outcomes and client value. We do more than traditional business process outsourcing. We do more than just “keeping the lights on.” We work shoulder-to-shoulder with clients and their customers, constantly adapting to the pace of change, to ideate, innovate, and embed continuous advantage at the heart of their operations. And we do it with the kind of drive and passion that comes from loving what you do—and who you do it with.

You are someone with these skills, experience and qualifications:

• Has 5+ years of professional experience building production-grade Python services and APIs
• Is fluent with Python fundamentals: asynchronous programming (asyncio), typing, packaging, dependency management, and performance profiling
• Builds reliable backends with FastAPI/Flask, REST/gRPC, and clean architecture patterns; comfortable with SQLAlchemy/ORMs and data modeling
• Writes high-quality, tested code: pytest, fixtures/mocking, linting/formatting, type checking, and code reviews; integrates with CI/CD
• Works confidently with Docker/containers, Git, and observability (structured logging, metrics, tracing) to support production operations
• Understands databases and messaging: Postgres/MySQL, Redis, and event/queue systems (e.g., Kafka/SQS)
• Applies security-first practices: secrets management, least-privilege access, input validation, secure coding, encryption at rest/in transit, and PII handling
• Communicates clearly, documents decisions, and collaborates effectively with product, security, risk, and compliance stakeholders

It would be great for you to have some of these nice to haves as well:

• Practical GenAI/LLM experience: integrating hosted LLM APIs (e.g., Azure OpenAI, OpenAI, Anthropic), prompt design, and token/cost management
• Retrieval-augmented generation (RAG): embeddings, chunking strategies, vector search (FAISS, pgvector, Pinecone), and orchestration frameworks (LangChain, LlamaIndex) or custom pipelines
• LLM application quality and safety: prompt/version management, evaluation frameworks (automatic and human-in-the-loop), guardrails, red-teaming, and safe output handling
• Optimization and reliability: latency and throughput tuning, caching/semantic caching, batching, function/tool calling, and fallback/model routing patterns
• Model customization: fine-tuning or parameter-efficient tuning (LoRA/QLoRA), adapter-based approaches, and model selection trade-offs (quality, latency, cost, compliance)
• Multimodal familiarity: using models that handle text with images or structured data where relevant to use cases
• Observability for GenAI: tracing, token/latency metrics, cost dashboards, and incident response for LLM-enabled services
• Cloud and platform experience (Azure/AWS/GCP), Kubernetes or serverless, infrastructure as code, and governance considerations for regulated environments (banking/financial services)

The salary range for this position is $72,000 - $138,000, and individuals may be eligible to participate in our bonus program. Deloitte is fair and competitive when it comes to the salaries of our people. We regularly benchmark across a variety of positions, industries, sectors, targets, and levels. Our approach is grounded on recognizing people's unique strengths and contributions and rewarding the value that they deliver.
Our Total Rewards Package extends well beyond traditional compensation and benefit programs and is designed to recognize employee contributions, encourage personal wellness, and support firm growth.  Along with a competitive base salary and variable pay opportunities, we offer a wide array of initiatives that differentiate us as a people-first organization. On top of our regular paid vacation days, some examples include: $4,000 per year for mental health support benefits, a $1,300 flexible benefit spending account, firm-wide closures known as "Deloitte Days", dedicated days of for learning (known as Development and Innovation Days), flexible work arrangements and a hybrid work structure.