Job Title: Senior AI/ML Engineer
Experience: 10+ Years
Location: Hyderabad, India
Employment Type: Full-time
Role Summary:
We are looking for a highly experienced Senior AI/ML Engineer with strong hands-on expertise in designing,
developing, deploying, and monitoring enterprise-scale AI/ML systems. The candidate must possess end-to-end
experience across the complete AI/ML lifecycle, including model development, deployment, observability,
governance, optimization, and production support.
Key Responsibilities:
• Lead development and deployment of enterprise-scale AI/ML and Generative AI solutions.
• Build and optimize end-to-end ML pipelines including experimentation, deployment, monitoring, and retraining.
• Develop scalable inference architectures, vector search systems, and RAG-based applications.
• Implement observability, monitoring, governance, and production support mechanisms for AI systems.
• Drive model lifecycle management including versioning, experimentation tracking, and CI/CD automation.
• Mentor engineering teams and establish AI/ML engineering best practices.
• Collaborate with business stakeholders to identify and implement AI-driven solutions.
• Optimize AI systems for scalability, latency, reliability, and cost efficiency.
• Lead development and deployment of enterprise-scale AI/ML and Generative AI solutions.
• Build and optimize end-to-end ML pipelines including experimentation, deployment, monitoring, and retraining.
• Develop scalable inference architectures, vector search systems, and RAG-based applications.
• Implement observability, monitoring, governance, and production support mechanisms for AI systems.
• Drive model lifecycle management including versioning, experimentation tracking, and CI/CD automation.
• Mentor engineering teams and establish AI/ML engineering best practices.
• Collaborate with business stakeholders to identify and implement AI-driven solutions.
• Optimize AI systems for scalability, latency, reliability, and cost efficiency.
Required Skills & Qualifications:
• Strong hands-on experience in Artificial Intelligence, Machine Learning, and Generative AI systems.
• Extensive experience in end-to-end ML lifecycle including data ingestion, feature engineering, model
development, validation, deployment, monitoring, and retraining.
• Hands-on expertise with Python, SQL, APIs, and ML frameworks such as Scikit-learn, TensorFlow, PyTorch,
Hugging Face, and LangChain.
• Experience with Vector Databases, RAG pipelines, semantic search, embeddings, and LLM orchestration.
• Strong expertise in MLOps tools including MLflow, DVC, Docker, Kubernetes, CI/CD pipelines, and model
versioning.
• Hands-on experience with observability, logging, tracing, monitoring, drift detection, and model performance
tracking.
• Experience building scalable cloud-native inference and AI deployment pipelines.
• Strong understanding of distributed systems, data engineering, and scalable AI infrastructure.
• Excellent stakeholder management and cross-functional collaboration skills.
• Experience with Azure Cloud Stack is a plus
Skills Required
- 10+ years of experience in AI/ML engineering
- Hands-on experience designing, developing, deploying, and monitoring enterprise-scale AI/ML and Generative AI systems
- End-to-end ML lifecycle experience (data ingestion, feature engineering, model development, validation, deployment, monitoring, retraining)
- Proficiency in Python
- Proficiency in SQL
- Experience building and consuming APIs
- Experience with Scikit-learn, TensorFlow, and PyTorch
- Experience with Hugging Face and LangChain
- Experience with Vector Databases, semantic search, embeddings, and RAG pipelines
- Experience with LLM orchestration
- Experience with MLOps tools: MLflow, DVC, Docker, Kubernetes, CI/CD pipelines, and model versioning
- Hands-on experience with observability: logging, tracing, monitoring, drift detection, and model performance tracking
- Experience building scalable cloud-native inference and AI deployment pipelines
- Strong understanding of distributed systems, data engineering, and scalable AI infrastructure
- Excellent stakeholder management and cross-functional collaboration skills
- Experience with Azure Cloud Stack
NationsBenefits Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NationsBenefits and has not been reviewed or approved by NationsBenefits.
-
Fair & Transparent Compensation — Pay is frequently characterized as decent or good for certain entry-level and frontline roles, with timely pay also highlighted. Compensation is sometimes positioned as competitive relative to the work performed in those positions.
-
Leave & Time Off Breadth — Unlimited PTO is described as available for some salaried roles, which can increase perceived flexibility. Paid holidays and paid time off are presented as part of the standard package for eligible employees.
-
Wellbeing & Lifestyle Benefits — A fitness stipend and occasional company-sponsored outings or training-related perks are included among the extra benefits. These additions can modestly strengthen the overall rewards experience beyond core insurance.
NationsBenefits Insights
What We Do
NationsBenefits® is a leading supplemental benefits company providing managed care organizations with innovative healthcare solutions helping to promote independence, health, and well-being for more than 20 million members across the U.S. When the company was founded in 2015 by Glenn Parker, M.D., we set out to disrupt the healthcare industry. In 2020, we rebranded to NationsBenefits to expand the company’s core offering and broaden the scope of our clinically focused services. Today, we surpass traditional benefit management programs by helping our health plan partners drive growth, improve outcomes, reduce costs, and delight members. Our best-in-class service model engages members in meaningful and measurable ways with technology-based solutions tailored to the unique needs of each population.
