Senior Manager

Incedo is a US-based consulting, data science and technology services firm with over 3000 people helping clients

from our six offices across US, Mexico and India. We help our clients achieve competitive advantage through

end-to-end digital transformation. Our uniqueness lies in bringing together strong engineering, data science, and

design capabilities coupled with deep domain understanding. We combine services and products to maximize

business impact for our clients in telecom, Banking, Wealth Management, product engineering and life science

& healthcare industries. 

Working at Incedo will provide you an opportunity to work with industry leading client organizations, deep

technology and domain experts, and global teams. Incedo University, our learning platform, provides ample

learning opportunities starting with a structured onboarding program and carrying throughout various stages of

your career. A variety of fun activities is also an integral part of our friendly work environment. Our flexible

career paths allow you to grow into a program manager, a technical architect or a domain expert based on your

skills and interests. 

Our Mission is to enable our clients to maximize business impact from technology by

• Harnessing the transformational impact of emerging technologies
• Bridging the gap between business and technology

The Senior Manager – Generative AI (GenAI) Engineering will play a pivotal role in driving the organization's AI-led product innovation and engineering execution.

Reporting to the Director / Senior Director – GenAI Engineering, this leader will be responsible for translating AI strategy into action, managing cross-functional engineering teams, and delivering GenAI-based solutions, frameworks, and proof-of-concepts (PoCs) across enterprise programs.

This role demands a hands-on engineering leader with strong expertise in AI/ML frameworks, full-stack product development, and cloud-native architectures (preferably AWS). The Senior Manager will guide a team of engineers, architects, and data practitioners, ensuring technical excellence, innovation, and delivery rigor.

The ideal candidate brings a product mindset, a passion for Experimentation AI-led transformation, and the ability to balance strategic thinking with deep technical execution.

1. AI Solution Delivery and Product Engineering

• Lead the design and implementation of  1-2 GenAI-driven solutions, PoCs, and client-facing prototypes aligned with the enterprise GenAI roadmap.
• Translate strategic AI initiatives into execution plans, managing delivery timelines, technical risks, and dependencies.
• Collaborate with the Director and teams to build AI accelerators, reusable components, and automation frameworks for internal and client use cases.
• Drive  the integration of Generative AI capabilities into existing systems and applications — including intelligent assistants, document automation, and code intelligence.
• Drive engineering quality, code reviews, and technical standards for AI solution delivery.
• Contribute to architecture discussions, ensuring solutions are scalable, secure, and aligned with organizational standards.

2. Technical Leadership and Hands-on Contribution

• Build GenAI solutions, LLM-based applications, and prompt engineering frameworks hands-on using Python, LangChain, Hugging Face, and related ecosystems.
• Lead experimentation with fine-tuning, embedding strategies, and RAG architectures for enterprise use cases.
• Act as the technical anchor within GenAI programs—able to guide teams and contribute directly when required.
• Participate in architecture reviews and ensure adherence to AI governance principles.
• Collaborate with data engineering and DevOps teams to ensure smooth AI/ML model deployment pipelines (MLOps / AIOps).

3. Talent Development and Team Leadership

• Manage and mentor a team of AI engineers, full-stack developers, and architects.
• Foster a learning culture, encouraging engineers to explore new GenAI tools, frameworks, and problem-solving methods.
• Conduct regular code walkthroughs, design reviews, and innovation sessions to enhance team capability.

4. Collaboration and Stakeholder Management

• Engage with clients and internal stakeholders to understand business problems and propose AI-driven solutions.
• Collaborate with cloud, security, and infrastructure teams to ensure smooth deployment of AI applications.
• Partner with leadership to present technical outcomes, PoC results, and capability showcases.

Technical Prowess

1. Generative AI and ML Expertise

• Hands-on experience with AI development frameworks: LangChain, LlamaIndex, Hugging Face, OpenAI APIs, PyTorch, TensorFlow.
• Experience in prompt engineering, RAG pipeline design, vector database integration, and LLM tuning.
• Exposure to Agentic AI architectures, AI guardrails, and self-healing systems.

2. Product and Platform Engineering

• Experience  in software product engineering, with at least 3–5 years in AI/ML solution delivery.
• Strong background in MACH Architecture, full-stack development, and cloud-native application design.
• Proficiency in Python, , Java, or similar technologies for backend; and React, Angular, or for frontend.
• Experience in DevOps/MLOps/AIOps pipelines, CI/CD, and containerized environments (Docker, Kubernetes).
• Proficiency in databases (SQL, NoSQL, graph, vector stores) and data modelling for AI use cases.

3. Cloud and Infrastructure Skills

• Strong command of AWS ecosystem (SageMaker, Bedrock, ECS, Lambda, Redshift, IAM, KMS).
• Experience deploying solutions on atleast one cloud ( AWS, Azure, or GCP) environments.

Experience and Background

• 12–16 years of professional experience in product engineering, digital solutions, or AI-led product development.
• Proven track record in leading teams, delivering AI/ML solutions, and managing engineering execution.
• Strong understanding of AI adoption frameworks, CoE practices, and engineering maturity models.
• Experience in client engagement, stakeholder communication, and technical consulting.
• Exposure to Agile methodologies, scrum leadership, and innovation-driven delivery.

Certifications (Preferred)

• AWS / Azure / GCP Certified Solutions Architect – Associate or Professional
• Generative AI or Applied AI Certification (AWS, Google Cloud, Microsoft)
• Scrum Master / SAFe Practitioner certification desirable
• TOGAF Foundation preferred for architecture understanding.

We value diversity at Incedo. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.