Staff AI/ML full Stack Engineer & LeadBelcan Corporation • Normal, Illinois, United States
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Staff AI/ML full Stack Engineer & Lead
Belcan Corporation
- Normal, Illinois, United States
- Normal, Illinois, United States
About
Seeking a fully remote, NON-US worker
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.
Key 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 containerised 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), including traditional and RAG applications and MLOps architectures on Databricks, AWS and Google.
Apply strong understanding of Agentic AI, frameworks, and best practices.
Required Qualifications
Bachelor’s degree in Computer Science (or equivalent, mandatory).
10+ years of enterprise‑grade cloud deployment experience and 5+ years in software development.
5+ years of experience with Databricks and AWS MLOps deployment.
Strong cloud experience to develop infrastructure software.
Architect end‑to‑end agentic pipelines and tools for the team.
Deep knowledge of deploying the entire architecture of ML applications, both traditional and RAG, from data ingestion to model deployment.
Define best practices for model serving, data pipelines, and MLOps strategies; 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 MLOps, CI/CD for AI, and production model monitoring.
Strong understanding of software architecture patterns, distributed systems, and scalable data pipelines.
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.
Experience in manufacturing and predictive maintenance (plus).
Background in controls engineering (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.
Belcan is an equal opportunity employer. Your application and candidacy will not be considered based on race, colour, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
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Languages
- English
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