AWS Cloud Engineer

About Encore Talent Solutions:

Encore Talent Solutions is a trusted professional services firm dedicated to helping organizations achieve their goals by providing exceptional talent solutions. We partner closely with our clients to understand their unique culture and operational needs, delivering proactive support during times of growth, transition, and change. Our mission is to connect top talent with meaningful opportunities to drive business success.

Job Description

We are seeking a Lead AI AWS Engineer who has built AI/ML applications in cloud to join our dynamic team. In this role, you will play a key part in hands-on development of retrieval-augmented generation (RAG) systems, fine-tuning LLMs, and AWS-native microservices that drive automation, insight, and governance in an enterprise environment. You ll design and deliver scalable, secure services that bring large language models into real operational use connecting them to live infrastructure data, internal documentation, and system telemetry. You will collaborate with cross-functional teams and stakeholders to deliver high-quality solutions in a fast-paced environment.

Key Responsibilities

• Develop and maintain modular AI services on AWS using Lambda, SageMaker, Bedrock, S3, and related components built for scale, governance, and cost-efficiency.
• Contribute to the end-to-end development of RAG pipelines that connect internal datasets (e.g., logs, S3 docs, structured records) to inference endpoints using vector embeddings.
• Fine-tune LLM-based applications, including Retrieval-Augmented Generation (RAG) using LangChain and other frameworks.
• Tune retrieval performance using semantic search techniques, proper metadata handling, and prompt injection patterns.
• Work within the software release lifecycle, including CI/CD pipelines, GitHub-based SDLC, and infrastructure as code (Terraform).
• Support the development and evolution of reusable platform components for AI/ML operations.
• Create and maintain technical documentation for the team to reference and share with our internal customers.
• Excellent verbal and written communication skills

Required Qualifications:

• 7-10 years of proven software engineering experience with a strong focus on Python and GoLang.
• Must have a strong background in document tokenization, embeddings, various word models (such as Word2Vec, FastText, TF-IDF, BERT, GPT, ELMo, LDA, Transformers), and experience with NLP pipelines.
• Direct, hands-on development of RAG, semantic search, or LLM-augmented applications, and using frameworks and ML tooling like Transformers, PyTorch, TensorFlow, and LangChain not just experimentation in a notebook.
• Deep expertise with AWS services, especially Bedrock, SageMaker, ECS, and Lambda.
• Proven experience fine-tuning large language models, building datasets, and deploying ML models to production.
• Demonstrated experience with AWS organizations and policy guardrails (SCP, AWS Config).
• Demonstrated experience in Infrastructure as Code best practices and experience with building Terraform modules for AWS cloud.
• Strong background in Git-based version control, code reviews, and DevOps workflows.
• Demonstrated success delivering production-ready software with release pipeline integration.
• Strong problem-solving and analytical skills.
• Excellent communication and teamwork abilities.

Preferred Qualifications

• AWS or relevant cloud certifications.
• Policy as Code development (i.e., Terraform Sentinel).
• Experience optimizing cost-performance in AI systems (FinOps mindset).
• Data science background or experience working with structured/unstructured data.
• Awareness of data privacy and compliance best practices (e.g., PII handling, secure model deployment).
• Experience with Node.js.
• Familiarity with Agile methodologies and DevOps practices.
• Advanced certifications or specialized training.

Work Environment & Location:

• Location: Remote
• Collaborative team environment with opportunities for professional growth.