Accountabilities:

As a Senior AI Engineer, you will lead the development and optimization of intelligent applications, ensuring they are scalable, reliable, and aligned with real-world business needs. Your responsibilities will include:

Design, develop, and deploy production-ready applications powered by large language models (LLMs), including GPT, Gemini, Claude, and other foundation models through platforms such as AWS Bedrock.

Architect, build, and optimize advanced retrieval-augmented generation (RAG) pipelines capable of processing and retrieving information from large-scale document repositories.

Implement and orchestrate multi-agent AI systems using AWS Bedrock Agents, AgentCore, and relevant agentic frameworks.

Develop scalable AI pipelines and integrate them with enterprise systems while maintaining performance, reliability, and operational efficiency.

Build robust backend services and APIs for AI applications using Python and modern development frameworks.

Implement containerization, deployment strategies, and infrastructure practices that support reliable AI application delivery.

Develop monitoring and observability solutions to measure AI system performance, response quality, reliability, and operational costs.

Design and refine prompts, templates, and advanced prompt engineering techniques to improve model behavior, accuracy, and consistency.

Evaluate and fine-tune models for specific use cases when appropriate, experimenting with configurations, hyperparameters, and architectural approaches.

Collaborate with product managers, data scientists, solution architects, engineers, and business stakeholders to translate complex requirements into effective technical solutions.

Stay informed about developments in generative AI research and assess emerging models, frameworks, and technologies for practical applications.

Contribute to technical documentation, engineering standards, best practices, and knowledge-sharing initiatives.

Participate in sales-related initiatives involving generative AI, helping communicate technical capabilities and potential solutions.

Requirements

The ideal candidate will have substantial software engineering experience, strong programming skills, and hands-on expertise in designing and delivering generative AI solutions. Relevant qualifications and capabilities include:

Significant professional experience in software engineering, ideally involving the development of complex, production-grade applications.

Full-stack development experience and the ability to work across backend services, APIs, and application integrations.

Hands-on experience with large language models, foundation models, and associated APIs.

Practical experience designing and implementing agentic architectures using frameworks such as LangChain, LlamaIndex, CrewAI, or AutoGen.

Strong knowledge of prompt engineering, prompt optimization, and techniques for improving LLM performance and output quality.

Experience building retrieval and knowledge systems for AI agents using vector databases such as Pinecone, Weaviate, or OpenSearch, along with embedding models or knowledge graphs.

Proficiency in Python and familiarity with modern frameworks and libraries used to develop AI-powered applications.

Experience with cloud-based AI platforms, particularly AWS Bedrock, and familiarity with models and services such as OpenAI SDK and Gemini.

Understanding of DevOps practices, containerization, and CI/CD pipelines for deploying and maintaining AI applications.

Ability to design scalable, maintainable, and reliable AI systems that integrate with enterprise environments.

Strong analytical and problem-solving skills, with the ability to evaluate alternative models and architectures and make informed technical decisions.

Excellent collaboration and communication skills, including the ability to work with multidisciplinary teams and translate business needs into technical solutions.

A proactive approach to continuous learning, experimentation, documentation, and knowledge sharing.

Benefits

Health and dental insurance: Access to healthcare coverage.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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