Python & Generative AI Technology Lead

Job Summary

Synechron is seeking a Python + AI Technology Lead to guide the design, development, and delivery of scalable software and artificial intelligence solutions. The role combines hands-on technical leadership with team management, stakeholder engagement, technology strategy, and delivery oversight.

The position will translate business requirements into secure, maintainable, and measurable technology solutions. The successful candidate will lead cross-functional teams, provide technical direction, evaluate emerging technologies, and maintain technology roadmaps aligned with Synechron’s business objectives.

This role contributes to business performance by improving delivery efficiency, enabling responsible adoption of AI, strengthening engineering practices, and supporting the development of reliable and sustainable technology platforms.

Software Requirements

Required Software Skills

• Python 3.10 or later: Minimum 5 years of professional development experience, including production-grade application development, automation, API development, testing, and performance optimization.

• AI and machine learning platforms: Practical experience developing, integrating, or deploying AI and machine learning solutions in production environments.

• Generative AI and large language model technologies: Experience with prompt design, retrieval-augmented generation, model evaluation, AI application development, and responsible AI controls.

• Version control systems: Minimum 5 years of experience using Git-based workflows, including branching strategies, pull requests, code reviews, and release management.

• Project management tools: Experience using tools such as Jira, Azure Boards, or equivalent platforms for backlog management, sprint planning, dependency tracking, and delivery reporting.

• Continuous integration and continuous delivery tools: Experience with CI/CD pipelines for automated testing, security checks, packaging, and deployment.

• Containerization and orchestration tools: Working experience with Docker and Kubernetes or equivalent technologies for packaging and operating applications.

• Cloud platforms: Practical experience with at least one major cloud platform, including cloud-native application development, identity management, networking, monitoring, and cost controls.

• Relational and non-relational databases: Experience with SQL-based databases, data modeling, query optimization, and at least one NoSQL or vector database.

• API development and testing tools: Experience with RESTful APIs, OpenAPI specifications, API testing, authentication, and service integration.

• Agile delivery tools and practices: Demonstrated experience using Agile methodologies, estimation techniques, sprint metrics, retrospectives, and iterative delivery practices.

Preferred Software Skills

• Experience with Python 3.12 or later and modern dependency management practices.

• Experience with AI and machine learning libraries such as PyTorch, TensorFlow, scikit-learn, pandas, NumPy, or equivalent tools.

• Experience with orchestration and workflow tools for AI and data pipelines.

• Experience with vector databases, embedding services, model registries, and model monitoring platforms.

• Experience with infrastructure-as-code tools such as Terraform or equivalent technologies.

• Experience with observability platforms covering logs, metrics, traces, alerting, and service-level indicators.

• Experience with data processing technologies for batch and streaming workloads.

• Experience with software architecture documentation tools and modeling standards.

• Experience with FinOps, cloud cost optimization, and resource utilization monitoring.

• Experience applying automated quality gates, static analysis, dependency scanning, and software composition analysis.

Overall Responsibilities

• Lead cross-functional technology teams delivering Python, AI, data, and cloud-based solutions.

• Define technical approaches, architecture decisions, delivery plans, and measurable outcomes for technology initiatives.

• Provide technical guidance, mentoring, code review support, and career development input for team members.

• Translate business requirements into secure, scalable, maintainable, and testable technology solutions.

• Establish engineering standards for coding, testing, documentation, deployment, observability, and operational support.

• Drive successful delivery of projects by managing scope, dependencies, risks, resources, timelines, and delivery quality.

• Identify process improvements and implement changes that reduce rework, improve cycle time, and increase delivery predictability.

• Evaluate new technologies and make evidence-based recommendations based on business value, security, scalability, maintainability, and cost.

• Develop and maintain technology roadmaps aligned with organizational priorities and measurable business outcomes.

• Manage vendor relationships, assess service performance, support contract negotiations, and monitor delivery against agreed commitments.

• Promote responsible AI practices, including privacy protection, transparency, human oversight, bias monitoring, and appropriate model governance.

• Support sustainable engineering practices by promoting efficient use of cloud resources, responsible data storage, and optimized compute consumption.

Performance Outcomes and Expectations

• Technology initiatives are delivered against agreed scope, timelines, quality measures, and risk controls.

• Solutions meet defined standards for security, reliability, scalability, maintainability, and operational readiness.

• Teams demonstrate improved delivery predictability, engineering consistency, and knowledge sharing.

• Technology roadmaps remain current and traceable to business priorities.

• AI solutions are evaluated using documented performance, safety, fairness, explainability, and operational criteria.

• Vendor performance, technology costs, a