Artificial Intelligence Developer

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About Serigor Inc.:

Serigor Inc., based in Maryland, is a CMMI Level 3 Woman-Owned Small Business (WOSB) specializing in IT services, staff augmentation, and government solutions. With over a decade of experience serving U.S. government agencies and Fortune 500 clients, Serigor delivers innovation-driven IT consulting in AI/ML, cloud, DevOps, Salesforce, and enterprise application development.

Role Overview:

hands-on AI developer

Key Responsibilities:

• LLM Development:

  Design and develop AI solutions using LLMs (e.g., OpenAI, Claude, LLaMA) to process complex documents like contracts, compliance records, and legal PDFs.

• Prompt Engineering & Optimization:

  Build, test, and iterate on prompts and templates to improve LLM output accuracy, consistency, and context relevance.

• Backend AI Application Development:

  Write robust Python code to integrate AI models into applications; work with frameworks like

  LangChain

  ,

  Transformers

  ,

  spaCy

  , or

  Haystack

  .

• Data Structuring & Transformation:

  Convert unstructured language into structured formats like JSON, key-value pairs, or semantic tags.

• RAG Implementation:

  Build Retrieval-Augmented Generation (RAG) pipelines using embeddings, vector databases (FAISS, Pinecone, Chroma), and retrievers.

• Tooling & Prototyping:

  Develop lightweight internal tools, dashboards, and utilities to test, visualize, and validate AI performance.

• Deployment Support:

  Work closely with DevOps teams or independently deploy AI APIs and services on cloud platforms or internal infrastructure.

• AI Evaluation:

  Design A/B tests, benchmarks, and validation suites to assess LLM performance, identify edge cases, and iterate improvements.

Required Skills & Qualifications:

• Experience:

  Overall 5 years in software development and 2+ years of hands-on experience in AI/ML/NLP application development.

• Programming:

  Strong Python skills and familiarity with AI libraries (Hugging Face, LangChain, PyTorch/TensorFlow, etc.).

• LLMs:

  Experience building applications using GPT, Claude, LLaMA, or similar models via APIs or hosted environments.

• Vector Search:

  Experience with vector databases like FAISS, Pinecone, or Weaviate.

• Document Intelligence:

  Working knowledge of document chunking, embeddings, metadata tagging, and semantic search.

• Prompt Engineering:

  Ability to write effective prompts and structured templates for production use.

• Version Control & Collaboration:

  Git, RESTful APIs, and collaboration in agile/dev squads.

Preferred Qualifications:

• RAG Systems:

  Prior experience developing Retrieval-Augmented Generation solutions.

• Cloud AI Services:

  Familiarity with OpenAI, AWS Bedrock/SageMaker, Azure OpenAI, or Google Vertex AI.

• LLMOps Exposure:

  Experience with LLMOps tools or workflow orchestration (e.g., LangSmith, Weights & Biases).

• Domain Exposure:

  Experience with legal, regulatory, or compliance-heavy document sets is a plus.