Job Description
Job Description
LeadStack Inc. is an award winning, one of the nation's fastest growing, certified minority owned (MBE) staffing services provider of contingent workforce. As a recognized industry leader in contingent workforce solutions and Certified as a Great Place to Work, we're proud to partner with some of the most admired Fortune 500 brands in the world.
Job Title: AI/ML Engineer
Duration:12 months
Location: Stanford, CA 94305 (Hybrid)
Position Overview
The AI/ML Engineer will be a key technical contributor driving CGOE’s AI transformation initiatives, with a focus on building and deploying intelligent, cloud-native applications including GenAI-powered systems, retrieval-augmented assistants, and data-driven automation workflows. Working at the intersection of machine learning, cloud engineering, and educational innovation, this role converts complex requirements into scalable, secure, and maintainable AWS-native AI systems that enhance teaching, learning, and operations across CGOE’s global online programs.
Top Requirements
- 3+ years deploying AI/ML applications in production environments.
- Strong experience with Python and AWS (serverless, microservices, CI/CD, IAM).
- At least one AWS Associate-level certification (e.g., Solutions Architect Associate, Developer Associate, SysOps Administrator Associate, Data Engineer Associate).
Key Responsibilities
AI Application & Systems Development
- Own the design and end-to-end implementation of AI systems combining GenAI, narrow AI, and traditional ML models (e.g., regression, classification).
- Implement retrieval-augmented generation (RAG), multi-agent, and protocol-based AI systems (e.g., Model Context Protocol/MCP) using modern frameworks such as LangChain and LlamaIndex or similar.
- Integrate AI capabilities into production-grade applications using serverless and containerized architectures (AWS Lambda, Fargate, ECS).
- Fine-tune and optimize existing models for specific educational and administrative use cases, focusing on performance, latency, and reliability.
- Build and maintain data pipelines for model training, evaluation, and monitoring using AWS services such as Glue, S3, Step Functions, and Kinesis.
Cloud & Infrastructure Engineering
- Architect and manage scalable AI workloads on AWS leveraging services such as SageMaker, Bedrock, API Gateway, EventBridge, and IAM-based security.
- Build microservices and APIs to integrate AI models into applications and backend systems.
- Develop automated CI/CD pipelines to ensure continuous delivery, observability, and monitoring of deployed workloads (e.g., GitHub Actions, CodePipeline).
- Apply containerization best practices using Docker and manage workloads via AWS Fargate and ECS for scalable, serverless orchestration and reproducibility.
- Ensure compliance with **(e.g., FERPA, GDPR-style requirements) for secure data handling and governance.
Collaboration, Culture & Continuous Improvement
- Collaborate with cross-functional teams (engineering, product, academic stakeholders, operations) to deliver integrated and impactful AI solutions.
- Use Git-based version control and follow code review best practices as part of a collaborative, agile workflow.
- Operate within an agile, iterative development culture, participating in sprints, retrospectives, and planning sessions.
- Continuously learn and adapt to emerging AI frameworks, AWS tools, and cloud technologies, contributing to documentation, internal knowledge sharing, and mentoring as the team scales.
Requirements
Education & Certifications
- Bachelor’s degree in Computer Science, AI/ML, Data Engineering, or a related field (Master’s preferred).
- At least one AWS Associate-level certification required; professional-level or specialty certifications (e.g., Machine Learning Specialty, Advanced Networking, Security) are a plus.
Experience
- 3+ years of experience developing and deploying AI/ML-driven applications in production environments.
- 2+ years of hands-on experience with AWS-based architectures (serverless, microservices, CI/CD, IAM).
- Proven ability to design, automate, and maintain data pipelines for model inference, evaluation, and monitoring.
- Experience with both GenAI and traditional ML techniques in applied, production settings.
Technical Skills
- Languages: Python (required); familiarity with Go, Rust, R, or TypeScript preferred.
- AI/ML Frameworks: PyTorch, TensorFlow, LangChain, LlamaIndex, or similar libraries for RAG and agentic workflows.
- Cloud & Infrastructure: AWS SageMaker, Bedrock, Lambda, ECS/Fargate, API Gateway, EventBridge, Glue, S3, Step Functions, IAM, CloudWatch.
- Infrastructure as Code: AWS CloudFormation.
- DevOps & Tools: Git, Docker, AWS Fargate, ECS, CI/CD (GitHub Actions, CodePipeline).
- Data Systems: SQL/NoSQL databases, vector databases, and AWS-native data services for AI workloads.
Desired Attributes
- Strong understanding of data engineering fundamentals and production-quality AI system design.
- Passion for applying AI to improve educational outcomes and operational efficiency.
- Excellent problem-solving, debugging, and communication skills.
- Demonstrated ability to learn rapidly, adapt to new technologies, and continuously improve.
- Commitment to ethical AI, data privacy, and transparency.
- Collaborative mindset with proven success in agile, team-based environments.
- Thrives in a fast-paced, evolving environment and proactively seeks opportunities to upskill and enhance processes.
Success Metrics
- Timely delivery of scalable, maintainable AI solutions that meet stakeholder needs.
- High system uptime, performance, and cost-efficiency of deployed workloads.
- Consistent adoption of best practices in CI/CD, monitoring, and version control.
- Positive stakeholder feedback and meaningful contributions to team documentation, learning, and innovation initiatives.
know more about current opportunities at LeadStack , please visit us on https://leadstackinc.com/careers/
Should you have any questions, feel free to call me on (513) 3184502 or send an email on waseem.ahmad@leadstackinc.com