Infosys is hiring AI Technical Lead

Required Qualifications

- Candidate must be located within commuting distance of Calgary, Canada or be willing to relocate to the area. This position may require travel in Canada.
- Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
- At least 4 years of Information Technology experience.
- Candidates authorized to work for any employer in the Canada without employer-based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time.

Required Skills
- 8+ years of overall technology experience with 5+ years in Contact Center and Conversational AI architecture.
- Architectural Leadership: Define and evolve the end-to-end architecture for RAG pipelines, agent frameworks, and distributed inference systems. Prioritize scalability, latency, and UX-aligned output determinism.
- Rigorous Evaluation: Build custom evaluation harnesses for AI agents, RAG, and LLM reasoning. Move beyond out-of-the-box metrics with domain-specific scoring, adversarial tests, and regression suites.
- Advanced AI Paradigms: Continuously integrate cutting-edge methodologies (structured reasoning, tool-use optimization, memory systems, multi-agent collaboration).
- Technical Mentorship: Coach developers on AI security, token-economics, UX patterns, and safe deployment practices. Establish coding standards and architectural guardrails
- Proven leadership delivering production-grade ML/AI systems.




- Strong foundations in vector math, LLM internals, embeddings, agent frameworks, and evaluation science.
- Knowledge of Google's GECX is a solid bonus.
- Expertise in systems-level programming, distributed architecture, and performance-critical code.
- Systems Architecture: Expertise designing distributed AI systems, multi-agent frameworks, and scalable RAG pipelines.
- LLM Internals: Deep understanding of transformer mechanics, attention patterns, tokenization, and inference optimization.
- Evaluation Science: Ability to design adversarial tests, regression suites, and domain-specific scoring functions.
- AI Security: Knowledge of jailbreak prevention, prompt-injection defense, secure tool-use, and zero-trust agent routing.
- Tokenomics: Ability to optimize token usage, context windows, and cost-latency trade-offs.
- Distributed Systems: Experience with load balancing, sharding, concurrency, and high-availability inference clusters. Observability: Familiarity with tracing, logging, telemetry, and agent-level debugging.
- DevOps for AI: CI/CD for model updates, containerization, GPU orchestration, and rollout strategies.
- Mentorship & Leadership: Ability to enforce engineering discipline, code quality, and architectural guardrails.
- Responsible AI & Governance: Guardrail design, content-safety policy, and audit/traceability for regulated deployments.

The job may also entail sitting as well as working at a computer for extended periods of time. Candidates should be able to effectively communicate by telephone, email, and face to face.

📌 AI Technical Lead (Calgary)
🏢 Infosys
📍 Calgary