AI Engineer

AI Engineer

Status Neo 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 Status Neo, we don't just talk about AI transformation. We build it — across engineering platforms, AI-native SDLC, agentic systems, and enterprise operating models.

Status Neo 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 Lang Chain, Lang Graph, 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:
  Lang Chain Lang Graph (preferred) RAG architectures Prompt Engineering AI Agents
• Hands-on experience with:
  Databricks Snowflake AWS (Bedrock, S3, Lambda, ECS/EKS, Sage Maker, 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, Health Tech, 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, Deep Eval, or Lang Smith.
• Familiarity with fine-tuning, embeddings, and model evaluation techniques.
• Exposure to multi-agent AI systems and agentic workflows.