Senior Python/AI Software Engineer

Compunnel Inc.; Phoenix (AZ); On-site; USD 150,000 - 230,000; Full time

Job summary

Compunnel Inc. seeks a Senior Python/AI Software Engineer to design, deploy, and scale secure AI solutions that support Information Security, Governance, and Technology Risk initiatives.

You will transform business requirements into production-grade AI systems using ML, Generative AI, and cloud-native architectures. You will build and optimize AI pipelines, containers, REST APIs, observability practices, and collaborate with Security, Risk, Engineering, Governance, and Data teams to deliver

Qualifications

• Bachelor's degree in CS/Engineering/Data Science or related field.
• 8+ years designing enterprise-scale software and AI/ML solutions.
• Hands-on experience developing AI/ML, Generative AI, or data-driven applications.
• Experience with AI and ML frameworks such as TensorFlow, PyTorch, scikit-learn, Flask, and FastAPI.
• Strong understanding of LLMs, NLP, embeddings, RAG, and prompt engineering.
• Experience with agentic AI frameworks such as LangChain, AutoGen, CrewAI, or similar.
• Experience developing and deploying AI applications using REST APIs.
• Experience with cloud platforms including AWS, Azure, and/or GCP.
• Experience with Docker, Kubernetes, and containerized deployment.
• Knowledge of vector databases such as pgVector, Milvus, or similar technologies.
• Experience with MLOps tools including MLflow, Kubeflow, Argo Workflows, or similar platforms.
• Experience with Kafka, Spark, NiFi, SQL, and NoSQL databases.
• Experience implementing CI/CD pipelines using Jenkins, GitLab CI, or XL Release.
• Familiarity with observability tools such as Prometheus, Elasticsearch, and Kibana.
• Strong understanding of software engineering best practices, system design, and scalable architecture.
• Excellent analytical, problem-solving, communication, and stakeholder collaboration skills.

Responsibilities

• Design, develop, and enhance AI/ML and Generative AI solutions using Python, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and agentic AI frameworks.
• Translate business, Information Security, Governance, and Technology Risk requirements into scalable AI applications.
• Develop, train, evaluate, and optimize machine learning models for NLP, classification, clustering, anomaly detection, and predictive analytics.
• Support the complete AI model lifecycle, including experimentation, evaluation, versioning, deployment, monitoring, and documentation.
• Build and maintain cloud-native AI pipelines using MLOps tools, APIs, Docker, Kubernetes, and modern deployment practices.
• Develop and integrate AI services using Flask, FastAPI, and RESTful APIs.
• Collaborate with Security, Risk, Engineering, Governance, and Data teams to deliver secure, reliable, and responsible AI solutions.
• Implement observability, monitoring, and performance optimization for AI applications.
• Participate in code reviews, testing, troubleshooting, and continuous improvement initiatives.
• Stay current with emerging technologies in ML, Generative AI, Agentic AI, MLOps, and responsible AI practices.

Skills

Python

AI/ML

LLMs

REST APIs

Docker

Kubernetes

MLOps

CI/CD

NLP

Education

Bachelor's degree in Computer Science, Engineering, Data Science, AI or related field

Tools

Flask

FastAPI

TensorFlow

PyTorch

scikit-learn

Docker

Kubernetes

MLflow

Job description

We are seeking a Senior Python/AI Software Engineer to design, develop, and deploy intelligent, secure, and scalable AI solutions supporting Information Security, Governance, and Risk initiatives. The ideal candidate will have extensive experience in Machine Learning, Generative AI, Agentic AI, and cloud-native AI application development, with the ability to transform business requirements into production-ready AI solutions.

Key Responsibilities

• Design, develop, and enhance AI/ML and Generative AI solutions using Python, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and agentic AI frameworks.
• Translate business, Information Security, Governance, and Technology Risk requirements into scalable AI applications.
• Develop, train, evaluate, and optimize machine learning models for natural language processing, classification, clustering, anomaly detection, and predictive analytics.
• Support the complete AI model lifecycle, including experimentation, evaluation, versioning, deployment, monitoring, and documentation.
• Build and maintain cloud-native AI pipelines using MLOps tools, APIs, Docker, Kubernetes, and modern deployment practices.
• Develop and integrate AI services using Flask, FastAPI, and RESTful APIs.
• Collaborate with Security, Risk, Engineering, Governance, and Data teams to deliver secure, reliable, and responsible AI solutions.
• Implement observability, monitoring, and performance optimization for AI applications.
• Participate in code reviews, testing, troubleshooting, and continuous improvement initiatives.
• Stay current with emerging technologies in Machine Learning, Generative AI, Agentic AI, MLOps, and responsible AI practices.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related field.
• 8+ years of experience designing and implementing enterprise-scale software engineering and AI/ML solutions.
• Strong hands-on experience developing AI/ML, Generative AI, or data-driven applications.
• Experience with AI and machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, Flask, and FastAPI.
• Strong understanding of Large Language Models (LLMs), Natural Language Processing (NLP), embeddings, Retrieval-Augmented Generation (RAG), and prompt engineering.
• Experience with agentic AI frameworks such as LangChain, AutoGen, CrewAI, or similar technologies.
• Experience developing and deploying AI applications using REST APIs.
• Experience with cloud platforms including AWS, Azure, and/or Google Cloud Platform (GCP).
• Experience with Docker, Kubernetes, and containerized application deployment.
• Knowledge of vector databases such as pgVector, Milvus, or similar technologies.
• Experience with MLOps tools including MLflow, Kubeflow, Argo Workflows, or similar platforms.
• Experience with Kafka, Spark, NiFi, SQL, and NoSQL databases.
• Experience implementing CI/CD pipelines using tools such as Jenkins, GitLab CI, or XL Release.
• Familiarity with observability tools such as Prometheus, Elasticsearch, and Kibana.
• Strong understanding of software engineering best practices, system design, and scalable application architecture.
• Excellent analytical, problem-solving, communication, and stakeholder collaboration skills.

Preferred Qualifications

• Experience deploying production-grade AI and machine learning systems in cloud-native environments.
• Knowledge of responsible AI principles and AI governance practices.
• Experience building scalable distributed AI platforms and enterprise AI solutions.
• Experience working in Agile software development environments.