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