AI Engineer
Statusneo
AI Engineer
StatusNeo is a global AI-native transformation firm helping enterprises design, engineer, and govern AI-led systems with trust at the core. We work with global enterprises across BFSI, retail, healthcare, airlines, and platform-driven industries to transform how software is built, operated, and scaled in an AI-first world. Our work is anchored in Authentic AI™ — an approach that treats AI not as a feature or experiment, but as a continuously evolving system that must be engineered with intent, accountability, and governance. At StatusNeo, we don't just talk about AI transformation. We build it — across engineering platforms, AI-native SDLC, agentic systems, and enterprise operating models.
StatusNeo is seeking a passionate and innovative AI Engineer to design, develop, and deploy cutting-edge AI and Generative AI solutions. The ideal candidate will have strong expertise in machine learning, large language models (LLMs), AI frameworks, and cloud-native technologies. You will work closely with product managers, data scientists, architects, and engineering teams to build intelligent systems that drive business value.
Responsibilities:
- Design, develop, and deploy production-ready Generative AI and LLM-powered applications.
- Build scalable Retrieval-Augmented Generation (RAG) pipelines using enterprise knowledge sources.
- Develop AI agents and workflow automation using LangChain, LangGraph, or similar orchestration frameworks.
- Integrate LLMs (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, etc.) into enterprise applications.
- Build and optimize data pipelines using Databricks, Snowflake, and AWS services.
- Design semantic search solutions using vector databases such as Pinecone, Weaviate, Chroma, or FAISS.
- Develop REST APIs and backend services to expose AI capabilities.
- Collaborate with data engineering teams to prepare, transform, and govern structured and unstructured healthcare data.
- Ensure AI solutions meet security, compliance, and privacy requirements, including HIPAA where applicable.
- Optimize model performance, latency, accuracy, and cost.
- Participate in architecture reviews, code reviews, and technical design sessions.
- Stay current with emerging AI technologies and recommend best practices for enterprise adoption.
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or a related field.
- 5+ years of software engineering experience.
- 3+ years of experience building AI/ML or Generative AI applications.
- Strong programming skills in Python.
- Experience building production applications using: LangChain LangGraph (preferred) RAG architectures Prompt Engineering AI Agents
- Hands-on experience with: Databricks Snowflake AWS (Bedrock, S3, Lambda, ECS/EKS, SageMaker, IAM)
- Experience with vector databases such as Pinecone, Weaviate, FAISS, Chroma, or Milvus.
- Experience integrating enterprise data sources and APIs.
- Knowledge of MLOps and model deployment best practices.
- Experience with Docker, Kubernetes, and CI/CD pipelines.
- Strong understanding of REST APIs and microservices architecture.
- Familiarity with Git and Agile development methodologies.
Preferred Qualifications:
- Previous experience in Healthcare, Life Sciences, HealthTech, or Health Insurance.
- Experience working with HIPAA-compliant systems and PHI.
- Knowledge of FHIR, HL7, Epic, Cerner, or other healthcare interoperability standards.
- Experience building AI-powered clinical assistants, patient engagement platforms, claims automation, or healthcare knowledge systems.
- Experience evaluating LLM performance using frameworks such as Ragas, DeepEval, or LangSmith.
- Familiarity with fine-tuning, embeddings, and model evaluation techniques.
- Exposure to multi-agent AI systems and agentic workflows.
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