Tech Lead Software Engineer - AI & Analytics

Job Summary

• Lead and motivate a Team of developers in the planning, delivery, and operation of highly reliable software. Accountable for the technical quality of the software that the Development Team produces and closely collaborates with the Business and other Stakeholders to ensure software meets functional and non-functional expectations. Act as an interface between the Development Team and Leadership, ensuring capacity and skillsets are aligned to meet ongoing delivery expectations. Time is allocated across Project Leadership, Technical Leadership/Mentoring, and Software Development/System Engineering.

Responsibilities

• Provide accurate development estimates in support of feasibility assessments and planned development activities
• Create, maintain, review and approve application designs in collaboration with Solution Architects and shared services Teams, ensuring alignment to the appropriate solution architectures and taking tradeoffs into account
• Develop, maintain, and review software with a focus on quality and maintainability
• Develop, maintain, review, and execute unit, functional, and integration tests with a focus on automation and test-driven development
• Provide technical oversight for performance testing, ensuring plan and outcomes align to expected non-functional requirements
• Plan and oversee application deployment activities and sequencing in non-production and production environments
• Investigate new technologies that could improve the applications and development activities
• Identify and resolve technical debt as appropriate, weighing the development effort against the value returned
• Mentor and coach Development Team on relevant architecture, design, development, and operations topics
• Evaluate code to ensure that it is valid, is properly structured, meets industry standards, and is compatible with browsers, devices, or operating systems
• May perform other job duties as directed by Employee's Leaders
• Architecture and development of large-scale cloud-native platforms and distributed systems (8+ years). AI/ML knowledge.
• Expert Python and backend engineering including APIs, microservices, event-driven architectures, and system design
• Strong AWS expertise across Lambda, ECS/EKS, S3, EventBridge, Step Functions, IAM, CloudWatch, and security
• Deep experience in observability, telemetry, logging, tracing, OpenTelemetry, monitoring, and Site Reliability Engineering
• Technical leadership, CI/CD, DevSecOps, architecture governance, performance optimisation, and mentoring
• Own the end-to-end platform architecture for telemetry, evaluations, observability, and Agentic AI Recommendations Platform.
• Lead engineering standards, technical direction, scalability, security, reliability, and platform evolution.
• Mentor engineers and drive adoption of modern cloud, AI, and observability engineering practices

Knowledge, Skills and Abilities

• Advanced knowledge of software development methodologies, practices, concepts, and technologies
• Advanced knowledge of at least one programming language and at least general knowledge of one or more additional programming languages
• Knowledge of project management methodology and principles
• Ability to demonstrate strong analytical and problem-solving abilities with a proactive mindset to get ahead of issues
• Skilled in communication with ability to articulate a clear direction and priorities on ideas, approaches, concepts, options, risks, impacts, and recommendations to technical, non-technical, and Leadership audiences with ability to adapt the message accordingly
• Ability to articulate the technical implementation and how it provides business value
• Ability to lead ideation, presentation, and group-thinking sessions
• Ability to influence effectively without authority up through Senior Leadership levels to achieve desired business outcomes
• Ability to lead multiple efforts concurrently, whether administrative or project related, while maintaining a successful level of completion in their own work
• Ability to work in a fast-paced, Team-based, Customer service-oriented environment
• Architecture and development of large-scale cloud-native platforms and distributed systems (8+ years). AI/ML knowledge.
• Expert Python and backend engineering including APIs, microservices, event-driven architectures, and system design
• Strong AWS expertise across Lambda, ECS/EKS, S3, EventBridge, Step Functions, IAM, CloudWatch, and security
• Deep experience in observability, telemetry, logging, tracing, OpenTelemetry, monitoring, and Site Reliability Engineering
• Technical leadership, CI/CD, DevSecOps, architecture governance, performance optimisation, and mentoring
• Agentic AI and LLM application architectures
• LangGraph, LangChain, MCP Frameworks
• Kafka, Kinesis, Streaming architectures
• Grafana, Datadog, Prometheus, PagerDuty

Education

• Required: Bachelor's degree in Computer Science, Engineering, Information Systems or related field and/or equivalent formal training

Experience

• Required: Expert level experience, expansive and far reaching knowledge in software engineering
• 8-10 years of relevant work-related experience
• Architecture and development of large-scale cloud-native platforms and distributed systems (8+ years). AI/ML knowledge.
• Expert Python and backend engineering including APIs, microservices, event-driven architectures, and system design
• Strong AWS expertise across Lambda, ECS/EKS, S3, EventBridge, Step Functions, IAM, CloudWatch, and security
• Deep experience in observability, telemetry, logging, tracing, OpenTelemetry, monitoring, and Site Reliability Engineering
• Technical leadership, CI/CD, DevSecOps, architecture governance, performance optimisation, and mentoring

Preferred Experience

• Agentic AI and LLM application architectures
• LangGraph, LangChain, MCP Frameworks
• Kafka, Kinesis, Streaming architectures
• Grafana, Datadog, Prometheus, PagerDuty

Other Qualifications

• Must meet confidentiality expectations as to confidential, proprietary and sensitive Company information
• Ability to work extended hours as needed
• Ability to work onsite approximately 3 days per week and as required by the business.