[Remote] AI/ML & Forward Deployed Engineer

Note: The job is a remote job and is open to candidates in USA. TALENT Software Services is recruiting an AI/ML and Forward Deployed Engineer for a contract role. The engineer will deliver end-to-end AI/ML and GenAI solutions, discover and deploy use cases with stakeholders, and build scalable, secure, observable production systems. Responsibilities include applied ML, LLM engineering, MLOps/LLMOps, API and frontend development, cloud infrastructure, data engineering, security, and technical leadership.

Responsibilities

• Deliver end-to-end AI/ML and GenAI solutions
• Combine applied machine learning, software engineering, and stakeholder problem-solving
• Build production-grade systems that are scalable, secure, observable, reliable, and aligned with business KPIs
• Work at the intersection of data, models, systems, and real users
• Thrive in ambiguous and fast-moving environments
• Partner with business, product, and customer stakeholders to identify and define AI opportunities
• Translate business requirements into AI use cases with success metrics, technical constraints, and rollout plans
• Conduct workshops and technical discovery covering feasibility, data readiness, integration requirements, and operational risks
• Drive rapid prototyping, pilot deployments, and iterative improvements based on user feedback
• Develop and improve ML solutions for classification, regression, ranking, forecasting, anomaly detection, and NLP
• Perform feature engineering, error analysis, model optimization, and performance tuning
• Establish robust ML evaluation practices, including offline metrics, validation strategies, experimentation, and A/B testing
• Build and productionize RAG (Retrieval-Augmented Generation) pipelines
• Work with document ingestion, chunking strategies, embeddings, retrieval tuning, reranking, and response grounding
• Implement GenAI guardrails and reliability patterns, including prompt templates, tool/function calling, hallucination reduction, citation strategies, and fallback mechanisms
• Build GenAI evaluation frameworks covering quality metrics, regression testing, safety testing, and human-in-the-loop workflows
• Package ML/LLM models into scalable services using Docker and Kubernetes
• Implement CI/CD pipelines for AI/ML workloads
• Manage the complete model lifecycle, including model registry, versioning, automated retraining, and governance workflows
• Build monitoring and observability for model drift, latency, throughput, errors, alerts, and rollbacks
• Apply DevOps and CI/CD best practices to ML workloads
• Develop scalable REST and gRPC APIs
• Build event-driven services and microservices
• Implement API integrations using OAuth2, JWT, and API Gateways
• Build and integrate AI-enabled user-facing applications
• Collaborate with Data Engineering teams to build reliable data pipelines
• Ensure data quality, data lineage, and data governance
• Design secure and compliant AI/ML solutions
• Apply security and compliance considerations throughout the development lifecycle
• Provide technical guidance and mentorship to engineering teams
• Lead architecture and design reviews
• Establish engineering and AI development best practices
• Create reusable templates, libraries, patterns, and accelerators
• Document solutions through architecture diagrams, runbooks, and operational playbooks

Skills

• Experience: 8+ years
• Required Experience: 6–8 years
• Experience with deep learning and production ML systems
• Experience with LLMs, Generative AI, and AI Agents
• Strong React.js experience
• Experience with Angular
• Experience with Azure API Management and Apigee
• Experience with Azure OpenAI
• OpenAI APIs
• LangChain
• Semantic Kernel
• RAG
• Prompt Engineering
• Embeddings
• Vector Databases
• Pinecone
• Azure AI Search
• Elasticsearch/OpenSearch
• Weaviate
• Milvus
• Experience with SQL and relational databases
• Experience with NoSQL databases
• Experience with Databricks / Spark
• MLflow
• Kubeflow
• Azure ML
• SageMaker
• Vertex AI
• Terraform
• ARM Templates
• Bicep
• Experience with forward-deployed/customer-embedded delivery
• HL7/FHIR experience
• Strong Azure experience
• MongoDB or Cosmos DB
• Healthcare or PBM (Pharmacy Benefit Management) experience
• HL7/FHIR knowledge

Benefits

• Remote work

Company Overview

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