AI Software Developer

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Who we are

CAI is a global technology services firm with over 8500 associates worldwide and a yearly revenue of $1 billion. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients colleagues and communities. As a privately held company we have the freedom and focus to do what is rightwhatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors and we are trailblazers in bringing neurodiversity to the enterprise.

Job Summary

Job Description

We are looking for an AI Software Developer to design build and maintain cloud-native backend services infrastructure and APIs that power AI features. This position will be full-time and hybrid.

What Youll Do

• Software Engineering & Cloud Infrastructure (Primary Focus) Design build and optimize cloud-native backend services (Python/) for AI applications on AWS or Azure (e.g. serverless containers managed services).

• Develop infrastructure as code (IaC) using Terraform CloudFormation or ARM templates to automate cloud deployments.

• Implement CI/CD pipelines for AI model deployment application updates and automated testing (e.g. GitHub Actions Azure DevOps).

• Build scalable APIs/microservices (FastAPI gRPC) to serve AI features (e.g. LLM inference agent workflows) with security latency and cost efficiency.

• Ensure reliability and observability via monitoring (Prometheus CloudWatch) logging and alerting for AI systems.

• AI Integration & Productionization (Secondary Focus) Integrate generative AI and agentic systems (e.g. LangChain CrewAI AutoGen) into full-stack applicationsnot just prototyping but productionizing workflows.

• Design RAG pipelines with vector databases (e.g. Azure Cognitive Search AWS OpenSearch) and optimize for latency/cost.

• Fine-tune LLMs (using LoRA PEFT) or leverage cloud AI services (e.g. AWS Bedrock Azure OpenAI) for custom use cases.

• Build data pipelines for AI training/inference (ingestion preprocessing synthetic data) with cloud tools (e.g. AWS Glue Azure Data Factory).

• Collaborate with ML engineers to deploy models via TorchServe Triton or cloud-managed services (e.g. SageMaker Endpoints Azure ML Endpoints).

• Collaboration & Ownership Work cross-functionally with product frontend and data teams to translate business needs into scalable AI solutions.

• Champion software best practices: testing (unit/integration) code reviews documentation and modular design.

• Mentor junior engineers on cloud engineering and AI system design.

What Youll Need

Required:

• 34 years of professional software development experience with strong fundamentals:

• Proficiency in Python (required) and modern frameworks (FastAPI Flask Django).

• Experience building cloud-native backend systems (AWS or Azure) with services like:

• Compute (EC2 Lambda Azure Functions VMs) Storage (S3 Blob Storage)

• Databases (RDS Cosmos DB DynamoDB) API gateways (API Gateway Azure API Management)

• Hands-on experience with containerization (Docker) and orchestration (Kubernetes).

• Proven track record in CI/CD pipelines infrastructure-as-code (Terraform/CloudFormation) and monitoring tools.

• 12 years of hands-on experience in AI application development specifically:

• Building generative AI or agentic workflows (e.g. using LangChain CrewAI AutoGen).

• Implementing RAG pipelines or fine-tuning LLMs in production (e.g. via AWS Bedrock Azure OpenAI or open-source models).

• Experience with cloud AI services (SageMaker Azure ML) or deploying open-source models on cloud infrastructure.

• Strong software engineering discipline:

• Writing testable maintainable code with unit/integration tests.

• Experience with Git workflows agile development and collaborative code reviews.

• Understanding of system design (scalability security cost optimization).

• Bachelors or Masters in Computer Science Software Engineering or related field.

Preferred:

• Experience with full-stack development (frontend frameworks like React/Vue for AI-powered UIs).

• Knowledge of serverless architectures (AWS Lambda/Azure Functions) for AI workloads.

• Familiarity with MLOps tools (MLflow Kubeflow) or cloud-native MLOps (SageMaker Pipelines Azure ML Pipelines).

• Prior work on cost-optimized AI systems (e.g. model quantization autoscaling spot instances).

• Contributions to open-source AI/ML projects or cloud infrastructure tooling.

Physical Demands

• Ability to safely and successfully perform the essential job functions

• Sedentary work that involves sitting or remaining stationary most of the time with occasional need to move around the office to attend meetings etc.

• Ability to conduct repetitive tasks on a computer utilizing a mouse keyboard and monitor

Reasonable accommodation statement

If you require a reasonable accommodation in completing this application interviewing completing any pre-employment testing or otherwise participating in the employment selection process please direct your inquiries to or (888).