Manage Consulting Expert- AI Architect

Design robust, scalable architectures for AI/ML systems, including LLM-based and generative AI solutions.
- Lead the implementation of AI features and services in enterprise-grade products with clear, maintainable code.- Develop solutions using LangChain, orchestration frameworks, and vector database technologies.- Collaborate with product managers, data scientists, ML engineers, and business stakeholders to gather requirements and translate them into technical designs.- Guide teams on best practices for AI system integration, deployment, and monitoring.- Define and implement architecture governance, patterns, and reusable frameworks for AI applications.- Stay current with emerging AI trends, tools, and methodologies to continuously enhance architecture strategy.- Oversee development of Proof-of-Concepts (PoCs) and Minimum Viable Products (MVPs) to validate innovative ideas.- Ensure systems are secure, scalable, and high-performing in production environments.- Mentor junior engineers and architects to build strong AI and engineering capabilities within the team.

Must to have Skills-
1316 years of overall experience in software development, with at least 5+ years in AI/ML system architecture and delivery.- Proven expertise in developing and deploying AI/ML models in production environments.- Deep knowledge of LLMs, LangChain, prompt engineering, RAG (retrieval-augmented generation), and vector search.- Strong programming and system design skills with a solid engineering foundation.- Exceptional ability to communicate complex concepts clearly to technical and non-technical stakeholders.- Experience with Agile methodologies and cross-functional team leadership.Programming Languages: Python, Java, Scala, SQL- AI/ML Frameworks: LangChain, TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers- Data Processing: Apache Spark, Kafka, Pandas, Dask- Vector Stores & Retrieval Systems: FAISS, Pinecone, Weaviate, Chroma- Cloud Platforms: AWS (SageMaker, Lambda), Azure (ML Studio, OpenAI), Google Cloud AI- MLOps & DevOps: Docker, Kubernetes, MLflow, Kubeflow, Airflow, CI/CD tools (GitHub Actions, Jenkins)- Databases: PostgreSQL, MongoDB, Redis, BigQuery, Snowflake- Tools & Platforms: Databricks, Jupyter Notebooks, Git, TerraformGood to have Skills-Solution Engineering and Implementation Experience in AI Project.

• AWS Machine Learning
• English
• GitHub
• Python
• Jenkins
• Kubernetes
• Prometheus
• Snowflake