What are the responsibilities and job description for the Gen AI Architect--Dallas, TX / Seattle, WA--Full Time position at OKAYA INFOCOM?
Title: Gen AI Architect
Location: Dallas, TX / Seattle, WA
Duration: Full Time
Job Description:
Must Have Technical/Functional Skills
- 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: LangChain, LlamaIndex, LangFlow, Langgraph, LangSmith, 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 (SentencePiece, Hugging Face Tokenizers), Fine-tuning Frameworks (Hugging Face Transformers, PyTorch Lightning)
- Datasets: HuggingFace Datasets, TensorFlow Datasets
- 3. LLMOps Proficiency
- Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions
- Monitoring & Management: Ray, SeldonCore, MLFlow, MLServer, Triton, BentoML, 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
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- Basic 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 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.
Salary : $180,000 - $200,000