Gen AI Architect
Job in
Seattle, King County, Washington, 98127, USA
Listed on 2026-06-13
Listing for:
Tata Consultancy Service Limited
Full Time
position Listed on 2026-06-13
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Job Description & How to Apply Below
- 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.
Roles & Responsibilities
- GenAI Application Development Expertise
- Programming
Languages:
Python
- Development Tools:
Lang Chain, Llama Index, Lang Flow, Langgraph, Lang Smith, Flowise
- Techniques: RAG Techniques
- Databases:
Vector Databases (Pinecone, Weaviate, Qdrant)
- Additional Technologies:
Knowledge Graphs, FastAPI, Streamlit, Gradio
- 2. Domain Model Fine-Tuning Capabilities
- Languages & Libraries:
Python, Data Engineering, OSS LLMs (Llama2, Mixtral, GPT-Neo, GPT-J)
- Tokenization & Frameworks:
Tokenizers (Sentence Piece, Hugging Face Tokenizers), Fine-tuning Frameworks (Hugging Face Transformers, PyTorch Lightning)
- Datasets:
Hugging Face Datasets, Tensor Flow Datasets
- 3. LLMOps Proficiency
- Infrastructure & CI/CD:
Dev Ops, Kubernetes, Docker, Git, Jenkins, Git Lab, Git Hub Actions
- Monitoring & Management:
Ray, Seldon Core, MLFlow, MLServer, Triton, Bento
ML, Prometheus, Grafana
- 4. Data Engineering for AI Applications
- Data Processing & Management:
Python, Apache Spark, Apache Kafka, AWS S3, Azure Data Lake Storage (ADLS), Delta Lake
- Workflow Automation:
Apache Airflow, dbt, Apache NiFi, Fivetran, Airbyte, Great Expectations
- Data Catalogs:
Amundsen, Collibra, Alation
- 5. AI-Ready Cybersecurity Knowledge
- 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
- 6. GenAI Guardrails and Ethics
- 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
- Transparency & Governance:
Model Interpretability Libraries, AI Governance Frameworks and Tools
- Basic Qualifications
- Bachelors degree in computer science, Data Science, or a related field; masters degree preferred.
- 5+ years of professional and/or postgraduate academic research experience in software engineering.
- Preferred experience in SAP / Salesforce or Oracle programs.
- 4+ year of experience designing and developing machine learning solutions.
- 3+ years of experience with cloud native engineering, AWS, Azure, Google.
Generic Managerial Skills, If any
- 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.
Base Salary Range : $160,000 to $200,000 Per Annum
TCS Employee Benefits
Summary:
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.
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