Software Engineer

Key Responsibilities
AI Application Development

Design, develop, and maintain AI-powered applications using Python.
Build intelligent applications leveraging OpenAI APIs, Amazon Bedrock, and other enterprise LLM platforms.
Design and implement Retrieval-Augmented Generation (RAG) architectures using enterprise knowledge sources and vector databases.
Develop Agentic AI workflows capable of autonomous reasoning, planning, and task execution.
Build reusable AI services, APIs, and software components for enterprise applications.
Optimize prompts, model interactions, and application performance for reliability, scalability, and cost efficiency.
Leverage AI development tools safely and effectively, taking ultimate human accountability for the design, security, and test coverage of all generated code.

Cloud & Infrastructure Engineering

Design, deploy, and maintain AI solutions on AWS.
Build Infrastructure as Code (IaC) using Terraform.
Develop containerized applications using Docker.
Deploy and manage workloads on Kubernetes.
Collaborate with DevOps engineers to automate deployments through CI/CD pipelines.
Ensure AI solutions meet security, scalability, and operational requirements. ‍

Software Engineering & Integration

Develop secure REST APIs and backend services.
Integrate AI capabilities with enterprise applications, cloud services, and external APIs.
Write clean, maintainable, well-tested, and reusable code following software engineering best practices.
Participate in architecture reviews, code reviews, and technical design discussions.

Innovation & Research

Evaluate emerging AI frameworks, tools, and technologies.
Prototype new AI capabilities and rapidly validate proof-of-concepts.
Recommend improvements that increase developer productivity and enhance customer outcomes.
Help establish reusable AI patterns, templates, and best practices across projects.

Documentation & Collaboration

Create technical documentation, architecture diagrams, implementation guides, and operational runbooks.
Work closely with Solution Architects, Cloud Engineers, Product Managers, and customers to translate business requirements into AI solutions.
Participate in Agile ceremonies, sprint planning, backlog refinement, and knowledge-sharing sessions.

Required Qualifications
Education & Experience

Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or related discipline (or equivalent professional experience).
4–8 years of professional software engineering experience.
2+ years of professional Python development experience.
Must be a U.S Citizen or Green Card Holder.
Technical Skills

Strong Python programming skills.
Efficient prompt engineering
Experience building applications on AWS.
Experience integrating OpenAI APIs and/or Amazon Bedrock.
Hands-on experience implementing Retrieval-Augmented Generation (RAG) solutions.
Experience designing or developing Agentic AI workflows.
Experience developing RESTful APIs.
Experience using Terraform for Infrastructure as Code.
Experience with Docker and Kubernetes.
Experience using Git and modern CI/CD pipelines.
Strong understanding of software design principles, API development, and cloud-native architectures.
Preferred Qualifications

Nice to have worked with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar AI orchestration frameworks.
Nice to have worked with vector databases such as Pinecone, Amazon OpenSearch, pgvector, or Weaviate.
Experience with Amazon ECS, Amazon EKS, Lambda, API Gateway, DynamoDB, or S3.
Familiarity with prompt engineering, AI evaluation, and model observability.
Experience with DevSecOps and secure software development practices.
Nice to have experience supporting U.S. Federal Government customers.
Familiarity with NIST 800-53, FedRAMP, FISMA, or CMS security requirements is a plus.
What We’re Looking For

Passion for solving complex business problems using AI.
Curiosity to learn and experiment with emerging AI technologies.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent written and verbal communication skills.
Ability to thrive in a collaborative, fast-paced Agile environment.
Customer-first mindset with a commitment to delivering high-quality software solutions.
Eligibility to Work at ArcheSys

All work must be performed within the continental United States.
Candidates must be legally authorized to work in the U.S. without sponsorship.
Selected candidates may be required to complete background investigations and obtain government security authorization for certain projects.
ArcheSys participates in E-Verify. ‍