AI Architect

Role: AI Architect

Location: Bangalore & Hyderabad

Mandatory Skill

• sAgentic Framework (Langgraph/Autogen/CrewAI
• )Prometheus/Grafana/ELK Stac
• kMachine Learning /Deep Learning Frameworks (TensorFlow/PyTorch/Keras
• )Hugging Face Transformer
• sCloud computing platforms (AWS/Azure/Google Cloud Platform
• )DevOps /MLOps /LLM Op
• sDocker, Kubernetes, DevOps tools like Jenkins and GitLab CI/CD
• .Fine Tuning of LLMs or SLMs (PALM2, GPT4, LLAMA etc
• )Terraform or CloudFormatio

1. Work on the Implementation and Solution delivery of the AI applications leading the team across onshore/offshore and should be able to cross-collaborate across all the AI stream

.2. Design end-to-end AI applications, ensuring integration across multiple commercial and open source tool

s.3. Work closely with business analysts and domain experts to translate business objectives into technical requirements and AI-driven solutions and applications. Partner with product management to design agile project roadmaps, aligning technical strategy. Work along with data engineering teams to ensure smooth data flows, quality, and governance across data source

s.4. Lead the design and implementations of reference architectures, roadmaps, and best practices for AI application

s.5. Fast adaptability with the emerging technologies and methodologies, recommending proven innovation

s.6. Identify and define system components such as data ingestion pipelines, model training environments, continuous integration/continuous deployment (CI/CD) frameworks, and monitoring system

s.7. Utilize containerization (Docker, Kubernetes) and cloud services to streamline the deployment and scaling of AI systems. Implement robust versioning, rollback, and monitoring mechanisms that ensure system stability, reliability, and performanc

e.8. Ensure the implementation supports scalability, reliability, maintainability, and security best practice

s.9. Project Management: You will oversee the planning, execution, and delivery of AI and ML applications, ensuring that they are completed within budget and timeline constraints. This includes project management defining project goals, allocating resources, and managing risk

s.10. Oversee the lifecycle of AI application development—from design to development, testing, deployment, and optimizatio

n.11. Enforce security best practices during each phase of development, with a focus on data privacy, user security, and risk mitigatio

n.12. Provide mentorship to engineering teams and foster a culture of continuous learnin

g.13. Lead technical knowledge-sharing sessions and workshops to keep teams up-to-date on the latest advances in generative AI and architectural best practice

s.Educati

:- Bachelor’s/Master’s degree in Computer Scien

ce- Certifications in Cloud technologies (AWS, Azure, GCP) and TOGAF certification (good to hav

e)Required Skil

ls:• The ideal candidate should have a strong background in working or developing agents using langgraph, autogen, and Crew

AI.• Proficiency in Python, with robust knowledge of machine learning libraries and frameworks such as TensorFlow, PyTorch, and Ker

as.• Understanding of Deep learning and NLP algorithms – RNN, CNN, LSTM, transformers architecture e

tc.• Proven experience with cloud computing platforms (AWS, Azure, Google Cloud Platform) for building and deploying scalable AI solutio

ns.• Hands-on skills with containerization (Docker) and orchestration frameworks (Kubernetes), including related DevOps tools like Jenkins and GitLab CI/

CD.• Experience using Infrastructure as Code (IaC) tools such as Terraform or CloudFormation to automate cloud deploymen

ts.• Proficient in SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra) to manage structured and unstructured da

ta.• Expertise in designing distributed systems, RESTful APIs, GraphQL integrations, and microservices architecture. - Knowledge of event-driven architectures and message brokers (e.g., RabbitMQ, Apache Kafka) to support robust inter-system communicatio