Technical Lead; Applied AI

X by 2 is a technology consulting firm specializing in healthcare and insurance transformation. For over 25 years, we have partnered with leading organizations across North America — from strategy and architecture to system modernization, data analytics, and AI — delivering high‑impact solutions from start to finish. We're agile, collaborative, and deeply committed to doing consulting the way it was meant to be done.

We are looking for a Technical Lead who will lead the design and development of AI solutions within enterprise environments for our clients. You'll combine hands‑on engineering with leadership, guiding architecture decisions, mentoring teams, and building solutions.

• Technical Leadership & Architecture

  • Lead architecture, design, development, testing, and deployment of enterprise software solutions (applications, data, integration, AI agents, AI models)
  • Participate in strategy and roadmap discussions, architecture definition, and technology evaluations
  • Mentor engineers through design reviews, code reviews, and technical guidance
  • Quickly evaluate and adopt new tools, technologies, and platforms to build prototypes and proofs‑of‑concept
  • Drive adoption of AI solutions and collaborate with engineering teams, product leaders, and domain experts to deliver results

• Software Engineering

  • Design, develop, and maintain scalable, production‑grade enterprise applications using modern languages and frameworks (Python, Java, C#, JavaScript)
  • Define and enforce coding standards, best practices, and design patterns across the team
  • Build and maintain CI/CD pipelines, infrastructure‑as‑code, and cloud‑deployed services (AWS, Azure)
  • Integrate enterprise systems via APIs, event‑driven architectures, and messaging platforms
  • Identify and resolve performance bottlenecks, technical debt, and system reliability issues

• Data & Analytics

  • Work with large, complex datasets and ensure data quality and integrity
  • Analyze data to generate insights that inform both model development and broader solution strategy
  • Collaborate with stakeholders to translate business problems into data‑driven solutions

• AI / Machine Learning Development

  • Design, develop, and train machine learning and deep learning models for healthcare and insurance use cases
  • Perform data modeling and feature engineering to support model development
  • Develop custom model metrics and approaches tailored to specific business problems
  • Ensure models are scalable, reliable, and integrated into production systems

• Agentic AI Development

  • Design and develop LLM‑powered workflows and agentic systems that help users complete complex tasks, retrieve information, reason over enterprise data, or interact with internal systems.
  • Integrate LLMs with tools, APIs, databases, documents, and enterprise platforms using patterns such as function calling, MCP, RAG, and structured tool use.
  • Architect orchestration patterns for planning, task decomposition, memory, context management, and human‑in‑the‑loop review where appropriate.
  • Develop orchestration layers to manage agent planning, memory, task decomposition, and execution loops
  • Evaluate agentic systems for correctness, reliability, safety, observability, auditability, and harden them for production readiness.
  • Stay current with emerging AI frameworks and platforms, selecting tools pragmatically based on client needs.

• Experience

  • 6+ years of experience in software engineering designing and developing enterprise applications, data/analytics solutions, and/or integration solutions
  • 1+ years of providing technical leadership as Tech Lead, Lead Engineer, or Architect
  • 1+ years in developing AI agents and/or AI model development and training

• Education

  • Bachelor's Degree in Computer Science, Software Development, Software Engineering, or Computer Engineering
  • (Optional) Master's Degree or Minor in AI/Machine Learning or Statistics

• AI Engineering Skills (Two or More)

  • Agentic AI: building and integrating autonomous AI agents using LLM APIs and orchestration frameworks (e.g., Anthropic Claude, OpenAI GPT, Lang Chain, CrewAI, Auto Gen, MCP)
  • Machine Learning & Deep Learning: developing and training models using standard ML/DL frameworks (e.g., Tensor…