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
Company H1B Sponsorship