Software Cloud Fullstack Developer

InDepth Engineering Solutions, LLC•Normal, IL

1d•Hybrid

About The Position

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.

Requirements

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
Architect end-to-end agentic pipelines and tools for others to contribute in the team
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
Hands-on model development and architectural design experience
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
Performing database selection and deployment (strong devops experience required)
End to End production level AI/ML product deployment experience

Nice To Haves

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
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

Responsibilities

Define system architecture, integration patterns, and technology standards for large-scale web and enterprise applications
Build and maintain robust, responsive applications using modern frontend frameworks (React, Vue, streamlit or Angular) and backend services in Python, Golang or RUST
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)
Develop RESTful and GraphQL APIs for internal and external integrations
Establish best practices for deployment pipelines, automated testing, and infrastructure-as-code (Terraform, Pulumi)
Drive system performance tuning, load balancing, and efficient code design
Coach and mentor engineers, conduct design/code reviews, and uphold engineering best practices
Partner with product, design, and business teams to deliver impactful solutions aligned with company objectives
Perform database selection and deployment (strong devops experience required)
Design ML and LLM stack (model hubs, vector DBs, embedding pipelines)
Deploy end-to-end architecture of ML applications, traditional and RAG applications
Design MLOPS architectures (Databricks, AWS, Google)
Apply strong understanding of Agentic AI, framework, best practices
Work with Databricks and AWS (mandatory)