AI ML Engineer / Malvern PA (Onsite) - FTE

Role:

AI/ML Engineer – Generative AI & AWS

Location:

Malvern, PA – Onsite

Job Type:

Full-Time / Permanent

Job Summary

We are seeking an experienced

AI/ML Engineer

with strong expertise in

Generative AI, Machine Learning, LLMs, and AWS cloud technologies

. The ideal candidate will be responsible for designing, developing, deploying, and optimizing scalable AI/ML solutions using

Amazon Bedrock, SageMaker, Python, RAG, AI Agents, and MLOps frameworks

.

The candidate will work closely with business, data engineering, and cloud teams to build secure, production-ready AI solutions that deliver measurable business value.

Must-Have Technical Skills

• Strong experience designing, developing, and deploying

AI/ML and Generative AI solutions on AWS

• Strong programming experience with

Python, PySpark, and SQL

• Hands-on experience with

Machine Learning, Deep Learning, and NLP

• Strong understanding of

Generative AI, LLMs, Prompt Engineering, and LLM application development

• Hands-on experience with

Amazon Bedrock and AWS SageMaker

• Strong experience building

RAG (Retrieval-Augmented Generation) pipelines

• Experience developing

AI Agents / Agentic AI solutions

• Hands-on experience with

LangChain, LangGraph, and/or LlamaIndex

• Strong knowledge of AWS services including:
• Amazon S3
• AWS Lambda
• IAM
• Amazon RDS
• CloudWatch
• Experience with

MLOps, MLflow, model lifecycle management, and CI/CD pipelines

• Experience with

Docker, Kubernetes, and Terraform

• Strong experience developing and integrating

REST APIs / FastAPI

• Experience with

model deployment, monitoring, performance tuning, and production support

• Understanding of

cloud-native architecture, security, scalability, and cost optimization

Key Responsibilities

• Design, develop, and deploy scalable

AI/ML and Generative AI solutions

using AWS services such as

Amazon Bedrock, SageMaker, Lambda, and S3

.

• Build and optimize

RAG pipelines, LLM-powered applications, AI Agents, and model inference workflows

.

• Develop data and ML pipelines to support

model training, evaluation, deployment, monitoring, and continuous improvement

.

• Implement

MLOps practices

and automated CI/CD pipelines for reliable and repeatable model deployments.

• Develop production-grade APIs and AI services using

Python and FastAPI

.

• Integrate LLMs with enterprise data sources, vector databases, APIs, and business applications.
• Evaluate and optimize model performance, latency, scalability, reliability, and cloud costs.
• Implement appropriate

security, IAM, monitoring, logging, and governance

practices for AI workloads.

• Containerize and deploy AI/ML applications using

Docker and Kubernetes

.

• Collaborate with

Data Engineers, Cloud Engineers, Architects, Product Owners, and business stakeholders

to translate business requirements into scalable AI solutions.

• Troubleshoot production issues and continuously improve AI/ML solutions based on performance and business requirements.
• Stay current with emerging developments in

Generative AI, LLMs, Agentic AI, AWS AI services, and MLOps

.

Leadership & Managerial Skills

• Strong

leadership, communication, and stakeholder management

skills.

• Ability to work effectively with

cross-functional and distributed teams

.

• Strong analytical and problem-solving abilities with a focus on delivering business outcomes.
• Ability to communicate complex

AI/ML concepts

clearly to both technical and non-technical stakeholders.

• Demonstrated ownership of projects from

solution design through production deployment and support

.

• Strong focus on

delivery excellence, quality, security, and continuous improvement

.

Preferred Qualifications

• Experience with

enterprise Generative AI implementations

in production environments.

• Experience with

vector databases, embeddings, semantic search, and knowledge bases

.

• Experience with

LLM evaluation, observability, guardrails, and responsible AI practices

.

• AWS certifications such as

AWS Machine Learning Engineer, AWS Solutions Architect, or equivalent

are a plus.

• Bachelor's or Master's degree in

Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field

.