Python
Machine Learning (ML)Job Description – AI Tech Lead
Location: Bangaluru
Experience: 10+ Years
Function: AI Center of Excellence (CoE)
Reporting To: Senior Vice President – CX / Head of AI CoE
We are seeking two highly experienced AI Tech Leads (AVP/DGM level) to drive the architecture, development, and delivery of large‑scale AI solutions spanning Predictive AI, GenAI, and Agentic AI across BPM, IT Services, Digital, Data Engineering, and Enterprise Transformation programs.
The role demands strong technical leadership, solution design capabilities, hands‑on execution ownership, and the ability to lead multi‑disciplinary teams to deliver scalable, production‑grade AI systems.
2. Key Responsibilities
A. Solution Architecture & Strategy
- Lead end‑to‑end solution architecture across Predictive AI, GenAI, Agentic AI, and enterprise data ecosystems.
- Partner with business and technology teams to define AI strategy, technical roadmaps, and implementation frameworks.
- Translate business goals into scalable AI architectures leveraging microservices, distributed systems, and modern AI toolchains.
- Own architectural decisions on model design, data pipelines, deployment frameworks, MLOps stack, and scaling strategies.
B. Project Delivery & Execution Leadership
- Drive the complete AI project lifecycle: Requirement Analysis → Architecture → Model Development → Engineering → Deployment → Monitoring.
- Lead AI engineering teams in developing production‑grade ML/GenAI/Agentic solutions with high reliability and performance.
- Establish and enforce engineering best practices, coding standards, DevOps/MLOps processes, and quality controls.
- Manage multiple concurrent AI initiatives with strong governance, risk mitigation, and stakeholder communication.
C. Technical Hands-on Expertise
- Architect and build complex AI systems involving:
- Large Language Models (LLMs) & GenAI apps
- Agentic workflows and autonomous task orchestration
- Predictive modeling, forecasting, optimization, and statistical modeling
- Knowledge graphs, vector databases, embeddings
- Data engineering pipelines (ETL/ELT) and cloud-native architectures
- Drive model evaluation, experimentation, benchmarking, A/B testing, and continuous improvements.
D. Team Leadership & Mentoring
- Lead and mentor a team of AI engineers, data scientists, MLOps engineers and developers.
- Build internal capabilities by establishing training, code reviews, reusable accelerators, and technical playbooks.
- Actively collaborate with product managers, data engineering teams, CX strategy teams, and domain SMEs.
E. Stakeholder & Client Management
- Act as a technology partner during client discussions, proposals, RFP responses, and solution demonstrations.
- Communicate complex AI concepts to CXOs, business leaders, and non-technical stakeholders seamlessly.
- Support pre-sales with solutioning, effort estimation, and technical presentations.
3. A. Technical Skills
- Strong proficiency in Python, cloud platforms (Azure/AWS/GCP), and AI frameworks (TensorFlow, PyTorch, LangChain, LlamaIndex).
- Hands-on experience building applications using:
- LLMs, RAG, fine‑tuning, prompt engineering
- Autonomous AI agents & multi-agent systems
- Predictive ML models (Regression, Classification, Clustering, NLP, CV)
- Expertise in microservices architecture, API design, scalable deployments.
- Strong command over SDLC, Agile methodologies, CI/CD, DevOps & MLOps.
- Experience with data engineering tools: Spark, Databricks, Airflow, Kafka, SQL/NoSQL, and modern data lakehouse platforms.
B. Functional & Domain Skills
- Experience working in BPM, Customer Experience, Digital Transformation, IT Services.
- Ability to map AI use cases to business value: workflow optimization, automation, customer experience, operations, and analytics.
C. Leadership & Soft Skills
- Strong team leadership and mentoring experience.
- Excellent communication, client-facing abilities, and stakeholder management skills.
- Strong decision-making, problem-solving, and delivery ownership.
4. Qualifications
- Bachelor’s / Master’s in Computer Science, Engineering, Data Science, or related fields.
- 10–15 years total experience with at least 5+ years leading AI/ML projects.
- Demonstrated success delivering large-scale AI programs in enterprise environments.
- Certifications in AI/ML, cloud, or architecture (preferred).
Shubham Vishwakarma
Full Stack Developer - Averlon
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