2 Llama Index Jobs

Position Summary: We value our talented employees, and whenever possible strive to help one of our associates grow professionally before recruiting new talent to our open positions. If you think the open position you see is right for you, we encourage you to apply! Our people make all the difference in our success. We leverage cutting edge Artificial Intelligence (AI) and Machine Learning (ML) algorithms to develop solutions for automated document processing and customer service chat bots. We are looking for AI Prompt Engineers with strong engineering, full stack expertise to build the best fit solutions leveraging Large Language Models (LLMs) and Generative AI solutions. Extreme focus on speed to market and getting Products and Services in the hands of customer and passion to transform healthcare is key to the success of this role. Build scalable software solutions using LLMs and other ML models to solve challenges in healthcare. Build enterprise grade AI solutions with focus on privacy, security, fairness. Work with Product Development as a Generative Artificial Intelligence (AI) subject matter expert and architect and develop scalable, resilient, ethical AI solutions Strong engineering skills to design the output from the AI with nodes and nested nodes in JSON or array, HTML formats as required This is critical so that the AI output can be consumed as is and displayed on the dashboard for accelerated development cycles. Build extensible API Integrations, low code UI UX solutions, with extremely short cycle times, to extract information from sources, integrate with GPT4, receive insights and make them available in intuitive, high performing dashboards Build solutions that align with responsible AI practices. Envision the solution outcomes to solve for the business problem with actionable insights and design viable solutions to meet the outcomes. Understand how AI is interpreting the data set and use that understanding to build prompts that lead to expected outcomes Architect and develop software or infrastructure for scalable, distributed systems and with machine learning technologies. Work with frameworks(Tensorflow, PyTorch) and open source platforms like Hugging Face to deliver the best solutions Optimize existing generative AI models for improved performance, scalability, and efficiency. Develop and maintain AI pipelines, including data preprocessing, feature extraction, model training, and evaluation. Develop clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders. Contribute to the establishment of best practices and standards for generative AI development within the organization. Experience Required: Overall 3+ years of experience 3 years of Full stack engineering expertise with languages like C#, Python and Proficiency in designing architecture, building API Integrations, configuring and deploying cloud services, setting up authentication, monitoring and logging Experience in implementing enterprise systems in production setting for AI, computer vision, natural language processing. Exposure to self-supervised learning, transfer learning, and reinforcement learning is a plus. Experience with information storage/retrieval using vector databases like pinecone. Strong understanding and exposure in natural language generation or Gen AI like transformers, LLMs, text embeddings. Experience with designing scalable software systems for classification, text extraction/summary, data connectors for different formats (pdf, csv, doc, etc) Experience with machine learning libraries and frameworks such as PyTorch or TensorFlow, Hugging Face, Lang chain, Llama Index. 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects. Programming experience in C C++, Java, Python. Strong knowledge of data structures, algorithms, and software engineering principles. Excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience. Possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Experience Desired: Familiarity with cloud-based platforms and services, such as AWS, GCP, or Azure. Hands on experience on tools products like Dynatrace, Splunk, Service Now preferred. Experience in identifying KPI on solution build using Generative AI, for Ex RAG based Q&A, data summarization, text content generation, data extraction, etc. will be a big advantage. Understanding of standards and regulation related to use of GenAI for a US based Health Insurance provider preferred. Healthcare experience (preferred but not mandate) Education and Training Required: Degree in Computer Science, Artificial Intelligence, or a related field.

What Youll Own Full Stack Systems: Architect and build end-to-end applications using Flask, FastAPI, Node.js, React (or Next.js), and Tailwind. AI Integrations: Build and optimize pipelines involving LLMs (OpenAI, Groq, LLaMA), Whisper, TTS, embeddings, RAG, LangChain, LangGraph, and vector DBs like Pinecone/Milvus. Cloud Infrastructure: Deploy, monitor, and scale systems on AWS/GCP using EC2, S3, IAM, Lambda, Kafka, and ClickHouse. Real-time Systems: Design asynchronous workflows (Kafka, Celery, WebSockets) for voice-based agents, event tracking, or search indexing. System Orchestration: Set up scalable infra with autoscaling groups, Docker, and Kubernetes (PoC ready, if not full prod). Growth-Ready Features: Implement in-app nudges, tracking with Amplitude, AB testing, and funnel optimization. Must-Haves: 1+ years of experience building production-grade full-stack systems Fluency in Python and JS/TS (Node.js, React) shipping independently without handholding Deep understanding of LLM pipelines, embeddings, vector search, and retrieval-augmented generation (RAG) Experience with AR frameworks (ARKit, ARCore), 3D rendering (Three.js), and real-time computer vision (MediaPipe) Strong grasp of modern AI model architectures: Diffusion Models, GANs, AI Agent Hands-on with system debugging, performance profiling, infra cost optimization Comfort with ambiguity fast iteration, shipping prototypes, breaking things to learn faster Bonus if youve built agentic apps, AI workflows, or virtual try-ons