Note: The job is a remote job and is open to candidates in USA. Further is a data, cloud, and AI company focused on helping businesses make informed decisions through data. They are seeking a Senior AI Engineer to lead the development of cloud-based AI products and bridge the gap between data science prototypes and production-grade software.
Responsibilities
- Lead the implementation of rigorous evaluation frameworks to monitor model performance, drift, and cost in real-time
- Architect and develop high-performance backend services and APIs using Python (FastAPI) to serve large language models at scale
- Design advanced Retrieval-Augmented Generation (RAG) systems, selecting and managing vector databases and optimizing embedding strategies for accuracy and speed
- Establish comprehensive model observability and guardrail systems to monitor real-time performance, detect distribution drift, and implement automated safety filters that mitigate hallucinations, bias, and toxic outputs in production environments
- Build robust integration layers that connect AI agents securely to external enterprise systems, CRMs, and legacy databases
- Conduct code reviews, provide technical guidance, and foster a culture of continuous learning and innovation within the engineering team
- Collaborate with infrastructure teams to define deployment strategies, ensuring solutions scale dynamically under load
- Define the end-to-end architecture for AI products on cloud platforms (preferably Google Cloud Platform), ensuring high availability, security, and cost-effectiveness
- Develop reusable internal libraries and architectural patterns and standards to accelerate the delivery of AI solutions across multiple client engagements
- Mentor engineers on best practices for building deterministic software around probabilistic AI models
Skills
- 6+ years of software engineering experience with at least 3 years dedicated to AI/ML application development
- Expert proficiency in Python AI application development and modern API architecture (REST, GraphQL, gRPC) using enterprise standards like static type checking and data validation
- Deep experience building production applications with LLM frameworks such as LangChain, LangGraph or LlamaIndex
- Hands-on expertise with vector databases (Pinecone, Weaviate, PostgreSQL) and search algorithms
- Strong understanding of LLMOps principles, including model registry, versioning, and serving infrastructure specifically in Google Cloud
- Experience in Typescript development for prototyping and integrations
- Proficiency with git workflows and understanding of standard application development processes
- Knowledge of advanced prompt engineering and fine-tuning techniques (LoRA, PEFT)
- Experience optimizing inference costs and latency for large-scale deployments
- Previous experience in a client-facing consulting role, managing diverse stakeholders and navigating complex organizational structures
- Any Google Cloud Professional Certification
Benefits
- Net-zero cost medical option
- Company contributions to your HSA
- Fertility support
- Fully-paid parental leave
- A monthly stipend for your lifestyle spending account
Company Overview
Company H1B Sponsorship