Gen AI Architect

Responsibilities Be an expert source on machine learning to drive delivery of new and innovative solutions. Propose creative solutions to approach business solutions with emerging technologies. Prototype new ways of applying technologies for solving business problems. Educate others so that they can demonstrate the innovative methods for achieving outcomes. Build and maintain machine learning principles, best practices, and code accelerators. Conduct external research and internal experimentation for machine learning techniques. Champion solution delivery behaviors and approaches from software engineers that accelerate delivery of reliable solutions and create a culture of teamwork. Analyze and communicate strategy, status, and product roadmaps to multiple audiences, including all levels of management. Technical Skills & Experience GenAI Application Development Expertise Programming Languages: Python Development Tools: LangChain, LlamaIndex, LangFlow, Langgraph, LangSmith, Flowise Additional Technologies: Knowledge Graphs, FastAPI, Streamlit, Gradio Languages & Libraries: Python, Data Engineering, OSS LLMs (Llama2, Mixtral, GPT-Neo, GPT-J) Tokenization & Frameworks: Tokenizers (SentencePiece, Hugging Face Tokenizers), Fine-tuning Frameworks (Hugging Face Transformers, PyTorch Lightning) Datasets: HuggingFace Datasets, TensorFlow Datasets Monitoring & Management: Ray, SeldonCore, MLFlow, MLServer, Triton, BentoML, Prometheus, Grafana Workflow Automation: Apache Airflow, dbt, Apache NiFi, Fivetran, Airbyte, Great Expectations Threat Modeling & Security: AI-Specific Threat Modeling Tools, Secure ML Pipeline Tools, API Security Tools Monitoring & Prevention: AI Security Monitoring Tools, Prompt Injection Prevention Libraries, Adversarial Example Detection Libraries Ethics & Fairness: AI Ethics Frameworks and Tools, Bias Detection and Mitigation Tools, Fairness Metrics Libraries Privacy & Security: Privacy-Preserving Machine Learning Libraries, Robustness and Security Tools Model Interpretability & Governance: Model Interpretability Libraries, AI Governance Frameworks and Tools Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions Data Engineering: Python, Apache Spark, Apache Kafka, AWS S3, Azure Data Lake Storage (ADLS), Delta Lake Data Catalogs: Amundsen, Collibra, Alation Qualifications Bachelor’s degree in computer science, Data Science, or a related field; master’s degree preferred. 5+ years of professional and/or postgraduate academic research experience in software engineering. Preferred experience in SAP / Salesforce or Oracle programs. 4+ years of experience designing and developing machine learning solutions. 3+ years of experience with cloud native engineering, AWS, Azure, Google. Managerial Skills Lead a team of junior developers. Ability to translate requirements into understandable technical design. Task effort estimation and distribution among team members. Excellent communication skills and stakeholder management. Ability to work with cross functional teams and business users. Compensation Base Salary Range : $160,000 to $200,000 Per Annum Benefits Discretionary Annual Incentive. Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans. Family Support: Maternal & Parental Leaves. Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement. Time Off: Vacation, Time Off, Sick Leave & Holidays. Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing. #J-18808-Ljbffr Tata Consultancy Services