Staff AI/ML Full Stack Lead Engineer

Job Title: Staff AI/ML Full Stack Lead Engineer

Location: Remote Employment Type: Full-time

Role Summary: We are seeking a Staff AI/ML solution lead to lead the architecture, design, and delivery of high-performance, enterprise-grade applications. This role combines deep hands-on coding with high-level architectural decision-making. You will work across frontend, backend, cloud infrastructure, database selection and integration layers, ensuring our systems are secure, scalable, and maintainable while enabling long-term technical growth. This hybrid role combines hands-on software engineering, devops and architectural leadership, enabling the delivery of robust, scalable, and innovative AI systems

Responsibilities:

• Architecture Leadership – Define system architecture, integration patterns, and technology standards for large-scale web and enterprise applications.
• Full Stack Development – Build and maintain robust, responsive applications using modern frontend frameworks (

React, Vue, streamlit or Angular) and backend services in Python, Golang or RUST.

• Cloud & Infrastructure – Architect cloud-native solutions leveraging AWS with a focus on scalability, security, and performance. Implement

containerized services with

Docker and orchestrate deployments using

Kubernetes (K8s).

• API & Service Design – Develop RESTful and GraphQL APIs for internal and external integrations .
• DevOps & CI/CD – Establish best practices for deployment pipelines, automated testing, and

infrastructure-as-code (Terraform, Pulumi).

• Performance Optimization – Drive system performance tuning, load balancing, and efficient code design.
• Technical Mentorship – Coach and mentor engineers, conduct design/code reviews, and uphold engineering best practices.
• Cross-Functional Collaboration – Partner with product, design, and business teams to deliver impactful solutions aligned with company objectives.
• Databases: Will be performing database selection and deployment (strong devops experience required)
• ML: Experience with both ML and LLM stack design (model hubs, vector DBs, embedding pipelines). The role required knowledge to deploy end-to-end architecture of ML applications, traditional and RAG applications, Design of the MLOPS architectures databricks, aws and google
• ML ops: Strong uderstanding of Agentic AI, framework, best practices
• Clouds: Databricks, AWS mandatory
• End to End production level AI/ML product deployment experience is required Qualifications

Must Have:

• At least bachelor’s in Computer Science mandatory
• 10+ years in deployment enterprise grade cloud level experience and 5+ years in software development
• 5+ years of experience with

Databricks and

AWS MLops deployment

• This role is more of a software lead and developer with strong

Cloud experience to develop infra software.

• Architect end-to-end agentic pipelines and tools for others to contribute in the team
• The role required knowledge to deploy end-to-end architecture of ML applications, traditional and

RAG applications.

• Architect end-to-end AI/ML systems from data ingestion to model deployment.
• Define best practices for model serving, data pipelines, and

ML-OPS strategies.

• engineering, including hands-on model development and architectural design.
• Expertise in traditional ML, deep learning, LLMs, embeddings, and RAG frameworks.
• Strong software engineering skills: Python, API development, microservices, database design, and version control (Git).
• Experience with cloud platforms (AWS, Databricks, Google) and containerized deployments (Docker, Kubernetes).
• Knowledge of

ML-OPS, CI/CD for AI, and production model monitoring .

• Strong understanding of software architecture patterns, distributed systems, and scalable data pipelines.
• Databases: Will be performing database selection and deployment (strong

devops experience required)

Preferred:

• Experience with

event-driven architectures and messaging systems (NATs, Kafka, RabbitMQ ).

• Familiarity with

authentication and authorization frameworks (OAuth2, JWT, SSO).

• Knowledge of

observability and monitoring tools (Prometheus, Grafana, OpenTelemetry).

• Background in designing large-scale enterprise or SaaS platforms.
• Python, Golang and Rust development experience is preferred
• Experience in manufacturing and predictive maintenance is a plus
• Background in controls engineering is a plus

Soft Skills

• Strong decision-making and problem-solving skills in high-stakes technical environments.
• Ability to lead and influence architectural direction across teams.
• Excellent communication with both technical and non-technical stakeholders.

Work Timings: Should be willing to work on CST Time zone