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The Applications Development Intermediate Programmer Analyst is an intermediate level position responsible for participation in the establishment and implementation of new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to contribute to applications systems analysis and programming activities.
Job Responsibility
Participation in the establishment and implementation of new or revised application systems and programs in coordination with the Technology team
Contribute to applications systems analysis and programming activities
Requirements
4-8 years of relevant experience in Apps Development or systems analysis role
Strong foundational knowledge in Machine Learning (ML modeling), Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and Large Language Models (LLMs)
Extensive hands-on experience with leading LLMs such as Google Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-source LLMs
Deep working knowledge and hands-on experience with Retrieval-Augmented Generation (RAG) pipelines, including advanced RAG techniques and their detailed implementation
Proven ability to build, tune, and deploy LLM-based applications using platforms like Vertex AI, Hugging Face, etc.
Expertise in developing robust prompt engineering strategies, prompt tuning, and creating reusable prompt templates
Hands-on experience with agentic framework-based use case implementation
Working knowledge of Guardrails and methodologies for assessing the performance and safety of GenAI features
Strong programming proficiency in Python, including extensive experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex
Proficiency in integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration tools
Hands-on experience with various vector databases (e.g., PG Vector, Pinecone, Mongo Atlas, Neo4j) for efficient data storage and retrieval
Experience in dealing with large amounts of unstructured data and designing solutions for high-throughput processing
Hands-on experience deploying GenAI-based models to production environments
Strong understanding and practical experience with MLOps principles, model evaluation, and establishing robust deployment pipelines
Strong expertise in CI/CD principles and tools (e.g., Jenkins, GitLab CI, Azure DevOps, ArgoCD) for automated builds, testing, and deployments
Proven experience with container orchestration platforms like OpenShift or Kubernetes for deploying, managing, and scaling containerized applications in a cloud-native environment
Strong problem-solving abilities, excellent collaboration skills for working effectively with cross-functional teams, and the capability to work independently on complex, ambiguous problems
Bachelor’s degree/University degree or equivalent experience