Additional Information
Job Summary
Synechron is seeking an accomplished Project/Program Manager specializing in GenAI initiatives to drive enterprise-level AI projects from inception through execution and deployment. The role involves managing cross-functional technical teams, engaging stakeholders, and ensuring successful delivery of proof-of-concept, pilot, and production solutions. This position plays a key role in aligning AI-driven strategies with organizational objectives, fostering innovation, and ensuring compliance with industry standards. The ideal candidate will leverage strategic leadership and technical oversight to maximize value from GenAI investments and support Synechron's digital transformation efforts.
Software Requirements
Required Skills:
Proven expertise in managing complex AI/ML projects, specifically GenAI models like large language models, transformers, embeddings, and Retrieval-Augmented Generation (RAG) techniques
Experience with DevOps, automation, and infrastructure tools supporting AI deployment (e.g., CI/CD, containerization)
Familiarity with project management tools such as Jira, Confluence, or equivalent
Strong understanding of AI/ML enterprise lifecycle, including data privacy, security, and compliance standards
Ability to interpret and communicate technical details around GenAI model architecture and deployment to both technical and non-technical stakeholders
Preferred Skills:
Knowledge of cloud platforms supporting GenAI, such as AWS, Azure, or GCP
Experience with AI model governance, bias mitigation, and encryption layers
Familiarity with AI automation tools and frameworks supporting rapid development cycles
Overall Responsibilities
Lead end-to-end GenAI project lifecycle, including planning, execution, delivery, and monitoring of PoCs, prototypes, and production solutions
Manage diversified technical teams across data science, engineering, and DevOps, fostering collaboration and best practices
Engage with internal and external stakeholders to define project scope, requirements, and success metrics
Develop project roadmaps, ensure on-time delivery, and manage risks and dependencies proactively
Oversee technical implementation, including AI model fine-tuning, deployment, and scaling in cloud environments
Drive automation and operationalization of GenAI workflows, supporting ongoing model monitoring and maintenance
Ensure compliance with data privacy, security standards, and ethical guidelines in AI deployment
Conduct research on emerging GenAI techniques and integrate best practices into ongoing projects
Advocate for continuous learning and knowledge sharing across teams and leadership
Technical Skills (By Category)
Programming Languages & Frameworks:
Required: Python (expert level), familiarity with AI frameworks such as PyTorch, TensorFlow, or similar
Preferred: C++, Java, or other languages supporting high-performance AI deployment
Model Development & Optimization:
Large Language Models (GPT, BERT, etc.), Embeddings, RAG, model fine-tuning, transfer learning, and encryption layers
Cloud & Infrastructure:
Deployment on AWS SageMaker, Azure Machine Learning, GCP Vertex AI, with experience managing cloud resources for AI workloads
DevOps & Automation:
CI/CD pipelines (Jenkins, GitLab CI), containerization (Docker), orchestration (Kubernetes), MLOps tools
Data & Security:
Knowledge of data privacy standards (GDPR, CCPA), model auditing, bias mitigation, encryption, secure API practices
Tools & Collaboration:
Jira, Confluence, Slack, Git, monitoring tools (Prometheus, Grafana, cloud-native solutions)
Experience Requirements
10+ years in project/program management within technology environments, with at least 1+ years in GenAI or advanced AI projects
Demonstrable experience leading AI/ML initiatives in enterprise contexts, from PoC to production
Proven experience in managing cross-disciplinary teams including data scientists, engineers, and DevOps professionals
Familiarity with cloud deployment, automation, and model governance practices
Industry experience in finance, healthcare, or customer-centric sectors supporting AI innovation is preferred
Day-to-Day Activities
Oversee planning, implementation, and delivery of GenAI projects aligned with business goals
Facilitate collaboration among data scientists, engineers, DevOps, and business stakeholders
Manage dependencies, risks, and issues proactively to ensure project success
Review technical architecture, and guide teams on best practices for model fine-tuning, deployment, and automation
Monitor operational performance, and optimize AI workflows for scalability and compliance
Conduct regular project status reporting, including risks, milestones, and outcomes
Drive innovation by researching latest AI/ML advancements and recommending new solutions