R&D Engineer 2, Software

Responsibilities

• Design & Development:

  • Build and optimize virtual assistant solutions leveraging

    LLMs

    ,

    RAG

    , and

    CAG

    frameworks.
  • Develop scalable APIs and microservices for chatbot and copilot integration.

• Data & Knowledge Management:

  • Implement

    vector databases

    , embeddings, and retrieval pipelines for context-aware responses.
  • Manage structured and unstructured data ingestion for knowledge bases.

• Model Integration & Optimization:

  • Fine-tune open-source or commercial LLMs for domain-specific tasks.
  • Implement prompt engineering and evaluation strategies for high-quality outputs.

• Software Engineering:

  • Write clean, maintainable, and efficient code in Python (preferred), Java, or similar languages.
  • Ensure CI/CD pipelines for model deployment and updates.

• Performance & Quality:

  • Develop evaluation metrics for chatbot accuracy, latency, and user experience.
  • Implement feedback loops for continuous improvement of VA responses.

• Collaboration:

  • Work closely with product managers, architects, and UX teams to align technical solutions with business goals.

Qualifications

• Education:

  Bachelor s or Master s in Computer Science, AI/ML, or related field.

• Technical Skills:

  • Strong programming skills in

    Python

    ,

    Java

    , or similar.
  • Experience with

    LLMs

    ,

    RAG/CAG architectures

    , and

    vector databases

    (e.g., Pinecone, Weaviate, FAISS).
  • Familiarity with

    LangChain

    ,

    LlamaIndex

    , or similar frameworks.
  • Knowledge of cloud platforms (Azure, AWS, GCP) and containerization (Docker, Kubernetes).

• AI/ML Expertise:

  • Understanding of NLP, embeddings, and transformer-based models.
  • Experience in fine-tuning and deploying models in production environments.

• Soft Skills:

  • Strong problem-solving and analytical skills.
  • Excellent communication and collaboration abilities.

• Design & Development:

  • Build and optimize virtual assistant solutions leveraging

    LLMs

    ,

    RAG

    , and

    CAG

    frameworks.
  • Develop scalable APIs and microservices for chatbot and copilot integration.

• Data & Knowledge Management:

  • Implement

    vector databases

    , embeddings, and retrieval pipelines for context-aware responses.
  • Manage structured and unstructured data ingestion for knowledge bases.

• Model Integration & Optimization:

  • Fine-tune open-source or commercial LLMs for domain-specific tasks.
  • Implement prompt engineering and evaluation strategies for high-quality outputs.

• Software Engineering:

  • Write clean, maintainable, and efficient code in Python (preferred), Java, or similar languages.
  • Ensure CI/CD pipelines for model deployment and updates.

• Performance & Quality:

  • Develop evaluation metrics for chatbot accuracy, latency, and user experience.
  • Implement feedback loops for continuous improvement of VA responses.

• Collaboration:

  • Work closely with product managers, architects, and UX teams to align technical solutions with business goals.