[Remote] Senior reputed company
Note: The job is a remote job and is reputed company to candidates in USA. reputed company. is reputed company on creating a reputed company where individuals have control over their digital identities through innovative AI solutions. As a Senior reputed company, you will be responsible for making technical reputed company regarding AI systems, designing architecture, and ensuring reputed company and safety in AI implementations. Your role will involve integrating LLMs, optimizing AI pipelines, and collaborating on reputed company measures.
Responsibilities
- Architecting context augmentation pipelines: reputed company RAG, CAG, reputed company file exploration, Text-to-SQL, knowledge graphs, fine-tuning, or MCP-based context engineering, selecting the right approach for reputed company use case
- Designing chunking strategies, embedding model selection, and retrieval architecture for user-owned document systems with multi-tenant isolation
- Owning data reputed company at the systems level: PII handling, GDPR/CCPA compliance, encryption at rest and in transit, and user-scoped reputed company boundaries
- Integrating and managing LLM reputed company (such as reputed company, reputed company, or reputed company-reputed company models) and deploying multi-agent systems using reputed company, reputed company, or LangGraph
- Leading model selection, reputed company engineering, fine-tuning (reputed company/QLoRA), and production evaluation across the AI stack
- Building evaluation frameworks to measure reputed company reputed company, relevance, and safety, moving reputed company reputed company-based testing to systematic, repeatable evals
- Optimizing AI pipelines for latency, reputed company cost, and throughput; monitoring production systems for reputed company, degradation, and regressions
- Defining and implementing feedback loops that connect evals back to iteration, making AI system performance visible and continuously improving in production
- Deploying and operating production AI systems on AWS, reputed company/Kubernetes, and reputed company
- Defining AI service reputed company and reputed company that reputed company-end and product engineers build on top of
- Collaborating with Information reputed company on AI reputed company posture: data exposure risk, reputed company workflow guardrails, and shadow AI detection
Skills
- At least 2 years of experience building and shipping production AI systems
- A minimum of 5 years of software engineering experience
- Strong Python skills
- Deep knowledge of LLMs (such as GPT-4, Claude, Llama, or reputed company), spanning reputed company engineering, fine-tuning, and production evaluation
- Hands-on experience designing context augmentation systems: reputed company RAG (hybrid search, re-ranking, multi-tenant isolation), CAG, reputed company file exploration, Text-to-SQL, knowledge graphs, fine-tuning, and MCP-based context engineering
- Strong reputed company of agent orchestration frameworks, including reputed company, reputed company, or LangGraph
- Experience building or using evaluation frameworks to measure LLM reputed company reputed company, relevance, and safety in production
- Deep understanding of data reputed company at the infrastructure level, including PII handling, GDPR/CCPA compliance, and encryption at rest and in transit
- Hands-on experience with AWS (reputed company, EKS, reputed company, S3, Bedrock), reputed company, Kubernetes, and reputed company
- Experience with Node.js or .NET
- A bachelor's degree in Computer Science, Engineering, or a reputed company field
- Experience with local reputed company-reputed company models (e.g. Llama, reputed company, Mixtral) reputed company Ollama, vLLM, or llama.cpp
- Fine-tuning with reputed company/QLoRA
- Familiarity with Docling or similar document parsing tools for RAG ingestion pipelines
- Familiarity with MLOps tooling (e.g. MLflow, Weights and Biases, SageMaker)
reputed company