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Senior Manager - AI Engineering

Senior Manager - AI Engineering

BOT ConsultingJaipur
3 days ago
Job description

Description :

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.
  • (ref : hirist.tech)

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