We are seeking a seasoned AI Architect and Engineering Leader with proven expertise in end-to-end AI solution development, deployment, and architecture across multiple domains.

In this dual-capacity role, you will be responsible for driving the AI technology strategy, leading execution, and managing a team of AI engineers and architects.

This role blends hands-on Technical Leadership with Strategic Delivery ownership ensuring innovation, scalability and client confidence across a growing portfolio of AI initiatives. It goes beyond building models its about anchoring BOTs AI practice, scaling talent and ensuring enterprise-grade outcomes from design to production.

Key Responsibilities :

Architecture & Technical Leadership :

- Define, design, and validate scalable, secure and high-performance AI architectures aligned with business goals and using AWS Bedrock, SageMaker, Lambda, Step Functions and other AWS-native services.

- Drive full-lifecycle AI solutioning data acquisition, feature engineering, model training, evaluation, deployment and monitoring.

- Evaluate existing AI and data infrastructure; identify gaps and propose modernization or optimization strategies.

- Lead proof-of-concepts and prototyping to assess new algorithms, frameworks and cloud AI services..

- Evaluate and integrate LLM orchestration frameworks (LangChain, LangGraph, Strands, AgentCore) for multi-agent and context-aware systems..

- Guide MLOps and AIOps pipelines model versioning, retraining, and monitoring using SageMaker, MLflow and custom APIs.

- Establish standards, frameworks, and reusable components for AI model deployment, inference and governance.

- Champion MLOps best practices CI/CD for ML, model registry, drift detection and automated retraining.

- Oversee AI system integration with cloud platforms (AWS, Azure, GCP), APIs and enterprise data systems.

- Guide architecture reviews and code quality checks to ensure technical excellence, maintainability and cost efficiency.

Management & Team Leadership :

- The leader will be both a technical visionary and a cultural steward, ensuring that India is not just an offshore hub, but a strategic extension of Caylent.

- As a leader, you will work as an anchor who will build the India Caylent GDC.

- Recruit, mentor, and manage a multidisciplinary team of AI engineers, ML scientists, data engineers, and MLOps specialists.

- Define team goals, KPIs and career growth paths aligned with organizational strategy.

- Allocate resources effectively, manage delivery timelines, and resolve technical dependencies or conflicts.

- Foster a culture of innovation, continuous learning and responsible experimentation.

- Conduct technical reviews, architecture sign-offs, and delivery governance for all AI engagements.

- Build partnerships across Cloud, Data, and Product teams to drive cross-functional collaboration.

- Represent the team in leadership forums; report delivery metrics, risks, and roadmap updates.

Operational Excellence & Governance :

- Define and implement AI governance standards - model lifecycle management, documentation, explainability, and bias mitigation.

- Ensure compliance with security and regulatory frameworks (GDPR, HIPAA, SOC2, EU AI Act, etc.) as relevant.

- Establish monitoring and observability for AI pipelines - model drift, data quality, latency, and cost.

- Drive AI FinOps - monitor compute utilization, optimize GPU/instance costs, and enforce budget accountability.

- Implement disaster-recovery and rollback strategies for production AI deployments.

- Champion ethical and responsible AI - establish review boards and feedback loops for transparency and fairness.

- Set up metrics dashboards (accuracy, precision, inference speed, ROI) to assess solution impact.

Stakeholder Engagement & Strategy :

- Collaborate with business and product leadership to align AI strategy with organizational objectives.

- Serve as the client-facing technical authority in AI engagements ensuring solution alignment and delivery confidence.

- Translate complex AI capabilities into clear business outcomes and client-facing value propositions.

- Contribute to pre-sales and solutioning for AI projects; contribute to proposals, estimations and architecture reviews.

- Serve as the AI thought leader and advisor to global teams, shaping enterprise-wide AI initiatives.

- Work with global leadership to evolve AI CoE capabilities frameworks, accelerators and reusable assets.

- Continuously evaluate AI industry trends (GenAI platforms, agentic workflows, domain-specific models) and lead internal adoption pilots.

Requirements :

Qualifications & Skills :

- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science or related field.

- 8+ years of total experience, with at least 5+ years in AI/ML solution architecture and delivery leadership.

- Proven experience leading end-to-end AI projects from design to production at scale.

- Deep understanding of machine learning, deep learning and MLOps workflows.

- Strong command of Python and modern AI/ML libraries (TensorFlow, PyTorch, Scikit-learn).

- Hands-on with cloud-native AI services AWS (Bedrock, SageMaker, Lambda, Step Functions), Azure ML, or GCP Vertex AI.

- Experience in microservice-based AI deployment, API design, and serverless or containerized inference (ECS/Fargate/Kubernetes).

- Working knowledge of data engineering pipelines, ETL orchestration and vector/feature stores.

- Familiarity with LLM and GenAI concepts (prompt engineering, RAG, embeddings) preferred but not mandatory.

- Strong understanding of software engineering and architecture principles - design patterns, scalability, fault tolerance and security.

- Demonstrated ability to make technical trade-offs and lead delivery under ambiguity.

- Excellent communication, people-management, and stakeholder-handling skills.

- Certifications: Preferred AWS Certified Machine Learning (Specialty), AWS Solutions Architect (Professional) or equivalent.

- Prior consulting or CoE leadership experience in AI/ML is an advantage.

Signs You May Be a Great Fit :

- Impact: Play a pivotal role in shaping a rapidly growing venture studio with Cloud-driven digital transformation.

- Culture: Thrive in a collaborative, innovative environment that values creativity, ownership, and agility.

- Growth: Access professional development opportunities and mentorship from experienced peers.

- Benefits: Competitive salary, wellness packages, and flexible work arrangements that support your lifestyle and goals.