Lead Software Engineer - Remote
About The Position
Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care’s most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together. Software engineering is the application of engineering principles to the design, development, implementation, testing, and maintenance of software systems using a disciplined and systematic approach. This role will lead primary development activities across Optum Technology, ensuring delivery of high-quality, scalable solutions supporting AI-driven voice, IVR, and conversational platforms. The role requires a solid focus on customer needs, product roadmap alignment, and continuous innovation, while embedding quality into every phase of the development lifecycle. The Lead Software Engineer will serve as a technical leader and subject matter expert, driving strategy, execution, and innovation across AI/ML-enabled platforms, with emphasis on AWS-based conversational systems. You’ll enjoy the flexibility to work remotely from anywhere within Canada (except for the Saskatchewan province) as you take on some tough challenges.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience)
- 10+ years of software engineering experience, including lead-level responsibilities
- 5+ years of experience designing and implementing cloud-native applications (AWS preferred)
- 3+ years of experience with: Amazon Connect and/or Amazon Lex (V2), AWS Lamba, API Gateway
- 2+ years of experience delivering AI / ML or conversational platform solutions in production environments
- Experience implementing automation, testing frameworks, and quality engineering practices
Nice To Haves
- Experience in healthcare technology or regulated environments
- Experience with CI/CD pipelines, DevOps practices, and observability tools
- Experience supporting enterprise AI transformation initiatives (e.g., AI 10.0)
- Exposure to voice platforms, IVR systems, and speech recognition technologies
- Familiarity with data-driven evaluation of AI/ML systems
- Proven advanced problem solving and analytical thinking
- Proven solid communication and stakeholder influence
- Proven ability to operate in a matrixed, enterprise environment
- Demonstrated innovation mindset with focus on continuous improvement
- Passion for emerging technologies and AI-driven solutions
Responsibilities
- Lead end-to-end execution across design, development, testing, deployment, and maintenance of AI-based software systems
- Provide technical leadership across engineering teams to ensure delivery of high-quality, scalable, and reliable code
- Review the work of others, provide guidance, mentorship, and technical oversight
- Serve as a subject matter expert and trusted advisor on complex engineering challenges
- Develop innovative approaches and influence future technology capabilities and architecture direction
- Lead end-to-end execution of AI/ML and conversational platform programs, from requirements through production and post-launch optimization
- Drive delivery of voice, IVR, and chatbot solutions using: Amazon Connect, Amazon Lex (V2)
- Partner with AI/ML teams to support: NLP pipelines, LLM integrations (Amazon Bedrock, OpenAI, or similar), Prompt engineering strategies
- Translate complex AI/ML concepts into actionable deliverables and clear leadership updates
- Architect and coordinate backend services leveraging: AWS Lambda, API Gateway, DynamoDB, Event-driven architectures
- Drive design and implementation of scalable, fault-tolerant cloud-based systems
- Ensure solutions meet performance, reliability, and scalability standards
- Drive program plans across multiple engineering teams, managing: Dependencies, Risks, Milestones, Technical trade-offs
- Forecast and plan resource requirements across workstreams
- Lead or support functional teams, projects, or enterprise initiatives
- Ensure operational readiness for production systems, including monitoring, support, and optimization
- Embed quality-first thinking across the software development lifecycle
- Define and enforce quality gates across: Functional performance, Reliability, AI/ML model accuracy
- Drive testing strategies for conversational AI, including: Intent accuracy, Dialog flow validation, Edge case handling, Regression testing
- Partner with QE teams to implement: Automated testing frameworks, Synthetic traffic generation, Replay-based validation (golden datasets)
- Use data-driven insights to continuously improve customer experience and system quality
- Evaluate and implement new tools, techniques, and engineering strategies
- Drive automation of common tasks and development of reusable utilities
- Authorize deviations from standards when necessary and recommend improvements
- Contribute to standards, methods, tooling, and best practices
- Influence enterprise direction for AI, cloud, and engineering innovation
- Anticipate customer needs and proactively develop solutions
- Serve as a key resource for complex and critical issues
- Perform advanced conceptual analysis and problem-solving
- Review and improve work delivered by others
- Provide clarity and guidance on highly complex topics
- Motivate, mentor, and inspire engineering teams
- Influence stakeholders and drive alignment across organizations
Benefits
- Flexibility to work remotely from anywhere within Canada (except for the Saskatchewan province)
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
