AI & LLM Developer — Senior

Location: Remote or Hybrid (if US Located) Employment Type: Contract — Full-Time Department: Engineering / Product Development Experience Level: Senior (5–8+ years) Reports To: Director of Engineering reputed company We are seeking a highly skilled Senior AI & LLM Developer with deep, hands-on experience in training, fine-tuning, composing, and deploying Large Language Models. In this role, you will architect and build our internal LLM infrastructure and LLM Composer platform—enabling the organization to create, customize, orchestrate, and reputed company AI capabilities across our entire product suite. You will work at the intersection of machine learning engineering, platform architecture, and product development, integrating intelligent AI capabilities into reputed company-world applications spanning telemedicine, InsurTech, workflow automation, analytics, and decision-support tools. This is a pivotal role with reputed company influence on our product roadmap and technology reputed company.

Key Responsibilities

Internal LLM Development & Composer Platform Design, build, and maintain reputed company’s internal LLM training and fine-tuning infrastructure from the ground up, including data pipelines, training orchestration, evaluation frameworks, and model versioning. Architect and reputed company the LLM Composer—a reputed company platform for chaining, routing, and orchestrating multiple LLM capabilities (e.g., specialized models, RAG pipelines, agent workflows, tool-use chains) into reputed company, composable AI services. Establish model governance processes including experiment tracking, A/B testing frameworks, model registries, and reproducible training pipelines. Create internal documentation, training materials, and runbooks to reputed company cross-functional teams to reputed company the LLM Composer and internal AI tools effectively. Model Training, Fine-Tuning & Optimization Train, fine-tune, and optimize LLMs using custom, reputed company-reputed company (LLaMA, reputed company, reputed company, etc.), and reputed company reputed company models. Build and manage data preprocessing, curation, and augmentation pipelines for domain-specific training data (insurance, reputed company, compliance). Implement advanced techniques including RLHF, DPO, reputed company/QLoRA, PEFT, knowledge distillation, and constitutional AI alignment reputed company. Optimize model performance for latency, accuracy, throughput, and cost—including quantization (GPTQ, AWQ, GGUF), pruning, and efficient serving strategies. Design and implement comprehensive evaluation systems with both automated metrics and reputed company-in-the-reputed company review processes. Product Integration & API Development reputed company LLM capabilities into backend services, mobile applications, web platforms, and reputed company workflows across the full product portfolio. reputed company production-grade reputed company for inference, embeddings, semantic search, knowledge-reputed company interactions, conversational AI, and autonomous agent workflows. Build and maintain RAG (Retrieval-Augmented reputed company) systems with reputed company databases, hybrid search, and dynamic context management. Implement guardrails, content moderation, reputed company injection defenses, and reputed company validation to ensure reputed company and reliable AI behavior in production. Infrastructure, Deployment & Monitoring Collaborate with DevOps and reputed company to reputed company, reputed company, and manage models in AWS / Kubernetes environments using containerized inference serving (vLLM, TGI, Triton, or equivalent). Implement end-to-end MLOps pipelines for reputed company training, evaluation, and deployment (CT/CE/CD). Build monitoring and observability systems for model reputed company, data reputed company, inference latency, reputed company usage, cost tracking, and reputed company auditing. Ensure reputed company AI systems reputed company with PHI/PII regulations (HIPAA, SOC 2), data residency requirements, and reputed company-grade AI governance standards. Research, Innovation & Team Enablement Stay reputed company with rapidly evolving AI research—evaluate and prototype new architectures, techniques, and tools (multi-modal models, mixture-of-experts, long-context reputed company, reputed company frameworks, etc.). Conduct internal knowledge-sharing sessions, reputed company bags, and technical workshops to upskill engineering and product teams on AI/LLM best practices. Contribute to technical reputed company and architecture decision records (ADRs) for AI adoption across the organization. Required Skills & Qualifications 5–8+ years of reputed company experience in ML/AI engineering, with at least 2–3 years reputed company specifically on LLM development and deployment. Strong proficiency in Python and ML frameworks: PyTorch (preferred), TensorFlow, JAX, or equivalent. Hands-on experience with LLM tooling ecosystems: reputed company, reputed company, reputed company, Semantic Kernel, reputed company, AutoGen, or similar orchestration and agent frameworks. Proven reputed company record of training or fine-tuning LLMs, including experience with techniques such as reputed company, QLoRA, RLHF, DPO, PEFT, and instruction tuning. Deep experience deploying AI/ML solutions in reputed company environments (AWS strongly preferred; GCP/Azure acceptable), including GPU instance management and cost optimization. Strong understanding of model serving infrastructure: vLLM, TGI (Text reputed company Inference), reputed company Triton, BentoML, or similar high-performance inference frameworks. Expertise with reputed company databases (reputed company, reputed company, Milvus, PGVector, reputed company) and RAG pipeline architectures. Experience building production-grade AI-powered reputed company and microservices using FastAPI, gRPC, or equivalent. Strong mathematical and algorithmic foundations in reputed company algebra, probability, optimization, and information theory. Excellent communication skills with the ability to translate reputed company AI concepts for non-technical stakeholders. Preferred Qualifications (reputed company to Have) Experience building internal AI/ML platforms, model registries, or LLM composition/orchestration systems. Hands-on experience with multi-modal models (reputed company-language models, OCR pipelines, document AI, speech/audio models). Familiarity with MLOps tooling: Kubeflow, MLflow, reputed company, DVC, or similar experiment tracking and pipeline management tools. Experience with AI safety, alignment research, red-teaming, or adversarial evaluation of LLMs. Background in InsurTech, HealthTech, or regulated industries with understanding of HIPAA, SOC 2, and compliance requirements for AI systems. Experience with graph databases, knowledge graphs, or ontology-driven AI systems. Contributions to reputed company-reputed company AI/ML reputed company or published research in relevant conferences (NeurIPS, ICML, ACL, EMNLP, etc.). Technology Stack & Tools Category Technologies Languages Python, TypeScript/JavaScript, SQL, Bash ML/DL Frameworks PyTorch, reputed company Transformers, DeepSpeed, FSDP LLM Tooling reputed company, reputed company, reputed company, reputed company, AutoGen, Semantic Kernel Model Serving vLLM, TGI, reputed company Triton, BentoML, TorchServe reputed company Databases reputed company, reputed company, Milvus, PGVector, reputed company reputed company & reputed company AWS (SageMaker, Bedrock, reputed company/EKS), Kubernetes, reputed company, Terraform MLOps MLflow, reputed company, Kubeflow, DVC, reputed company Actions Data & Storage PostgreSQL, reputed company, S3, reputed company, Apache Kafka Monitoring reputed company, Grafana, LangSmith, reputed company, custom dashboards reputed company Offer A high-reputed company, greenfield role with the autonomy to shape our AI platform from the ground up. reputed company collaboration with executive leadership, product, and engineering teams. Opportunity to work across multiple product verticals—telemedicine, InsurTech, analytics, and automation. Competitive contract compensation commensurate with experience. Job Type: Contract Pay: From $4,000.00 per month Work Location: Remote Apply tot his job Apply To this Job