Description :

Location : Hyderabad (Hybrid)

Job Description :

Responsibilities :

Technical Leadership & Architecture :

- Design and architect end-to-end AI and data engineering solutions that meet enterprise-scale requirements

- Lead the development of proof-of-concepts (POCs) for AI initiatives, ensuring rapid prototyping and validation of technical approaches

- Establish technical standards, best practices, and architectural patterns for AI and machine learning implementations

- Evaluate and recommend AI/ML technologies, frameworks, and platforms aligned with client needs and industry trends

- Oversee data pipeline architecture, ensuring scalable, secure, and efficient data processing workflows

- Drive MLOps practices implementation, including deployment pipelines, and monitoring systems

Client Engagement & Solutions :

- Collaborate directly with clients to understand business requirements and translate them into technical AI solutions

- Present technical proposals, solution architectures, and POC results to client stakeholders and C-level executives

- Lead technical discovery sessions and requirements gathering workshops with client teams

- Provide technical consultation on AI strategy, roadmaps, and implementation approaches

- Ensure the successful delivery of AI projects from conception through production deployment

- Act as the primary technical point of contact for enterprise AI engagements

Team Development & Mentorship :

- Mentor and guide data scientists, ML engineers, and data engineers in technical best practices

- Conduct technical training sessions and knowledge transfer workshops for internal teams

- Review and provide feedback on technical designs, code implementations, and architectural decisions

- Foster a culture of innovation and continuous learning within the AI practice

- Identify skill gaps and recommend training programs for team capability enhancement

- Lead cross-functional collaboration between AI, engineering, and business teams

Strategic Initiatives & Management Collaboration :

- Work closely with senior management to develop and execute AI practice strategy

- Provide technical insights and recommendations for business development and partnership opportunities

- Contribute to go-to-market strategies for AI solutions and service offerings

- Participate in strategic planning sessions and provide technical feasibility assessments

- Drive innovation initiatives and research partnerships with academic institutions and technology vendors

- Support pre-sales activities with technical expertise and solution positioning

Industry Representation & Thought Leadership :

- Represent Company at AI industry conferences, technical forums, and professional events

- Deliver keynote presentations, technical talks, and panel discussions at industry gatherings

- Author technical white papers, blog posts, and thought leadership content on AI trends and best practices

- Build and maintain relationships with AI community leaders, researchers, and technology vendors

- Participate in industry standards committees and AI ethics discussions

- Monitor and analyze emerging AI technologies and their potential business applications

Qualifications :

- Bachelors or Master's in Computer Science, Data Science, Machine Learning, or related technical field

- Minimum 10-12 years of experience in data engineering, machine learning, or AI solution development

- 5+ years in senior technical or architectural roles with client-facing responsibilities

- Proven track record of leading large-scale AI/ML implementations in enterprise environments

- Experience with end-to-end ML lifecycle from data collection to model deployment and monitoring

- Deep expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, etc.)

- Strong programming skills in Python, R, Scala, or Java with focus on production-quality code

- Extensive experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services

- Proficiency in big data technologies (Spark, Hadoop, Kafka, Databricks, Snowflake)

- Knowledge of containerization and orchestration tools (Docker, Kubernetes, MLflow)

- Experience with data pipeline tools (Airflow, Prefect, Azure Data Factory, etc.)

- Understanding of database systems (SQL, NoSQL, Vector databases, Graph databases)

- Familiarity with generative AI, LLMs, and foundation model architectures

- Exceptional communication skills with ability to explain complex technical concepts to non-technical stakeholders

- Strong presentation and public speaking abilities for client meetings and industry events

- Demonstrated leadership experience in mentoring technical teams and driving cross-functional initiatives

- Project management experience with Agile/Scrum methodologies and enterprise delivery frameworks

- Strong analytical and problem-solving skills with systems thinking approach

- Experience in consulting or client-services environments with proven client relationship management

- Industry certifications in cloud AI/ML platforms (AWS ML Specialty, Google Cloud ML Engineer, Azure AI Engineer)

- Experience with specific industry domains (healthcare, finance, retail, manufacturing) and their AI applications

- Published research papers, patents, or technical publications in AI/ML field

- Active participation in open-source AI/ML projects and communities

- Speaking experience at technical conferences or industry events

- Knowledge of AI ethics, responsible AI practices, and regulatory compliance (GDPR, CCPA, etc.)

- Experience with edge computing, IoT, and real-time AI applications

- Background in computer vision, NLP, or other specialized AI domains

Key Performance Indicators :

- Successful delivery of AI POCs and their transition to production systems

- Client satisfaction scores and successful renewal of AI engagement contracts

- Team development metrics including skill advancement and retention rates

- Industry recognition through speaking engagements, publications, and thought leadership activities

- Contribution to business growth through technical pre-sales support and solution development

- Innovation metrics including new solution development and technology adoption rates