AI Software Engineer
Quick Overview
Job Description
TECHNOGEN, Inc. is a Proven Leader in providing full IT Services, Software Development and Solutions for 15 years.
TECHNOGEN is a Small & Woman Owned Minority Business with GSA Advantage Certification. We have offices in VA; MD & Offshore development centers in India. We have successfully executed 100+ projects for clients ranging from small business and non-profits to Fortune 50 companies and federal, state and local agencies.
Position: AI Software Engineer
Work Model: Onsite/Hybrid Preferred | Remote may be considered for exceptional (top-notch) candidates.
We are seeking an experienced AI Software Engineer to join a team building next-generation AI-powered applications and platforms. This role is ideal for engineers who combine strong software engineering fundamentals with hands-on experience developing and deploying Generative AI solutions in production environments.
What You'll Do
- Design, build, and deploy scalable AI-powered applications and services
- Develop and optimize Retrieval-Augmented Generation (RAG) systems
- Build AI agents, workflow automation solutions, and intelligent assistants
- Integrate LLMs such as OpenAI, Claude, Gemini, and open-source models into production systems
- Design APIs, microservices, and cloud-native architectures
- Implement vector database solutions and knowledge retrieval pipelines
- Establish monitoring, evaluation, guardrails, and observability for AI systems
- Collaborate with cross-functional teams to deliver secure, reliable, and scalable solutions
Required Qualifications
- Strong software engineering background with Python, Java, Go, or TypeScript
- Experience building production-grade AI/GenAI applications
- Hands-on experience with:
- OpenAI, Claude, Gemini, Llama, or similar LLMs
- LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or related frameworks
- RAG architectures and vector databases (Pinecone, Weaviate, Qdrant, Chroma, Milvus)
- Experience with cloud platforms (AWS, Azure, or Google Cloud Platform)
- Knowledge of APIs, distributed systems, microservices, and scalable architecture
- Strong debugging, testing, and code review skills
Preferred Qualifications
- AI Agent development and orchestration
- Prompt engineering and evaluation frameworks
- LLM observability and monitoring tools
- MLOps, Kubernetes, Docker, CI/CD, and Infrastructure as Code
- Experience with enterprise AI deployments and governance
Skills
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