hackajob
AI Engineer / Machine Learning Engineer
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Role: AI Engineer - Generative and Agentic AI
hackajob is collaborating with Version 1 to connect them with exceptional professionals for this role.
As an AI Engineer focused on Generative and Agentic AI, you will design, build, deploy, and operate production-ready AI systems, taking ideas from early prototypes through to reliable, enterprise-grade solutions. You will work hands-on with real customer and internal use cases, owning the full lifecycle from design and orchestration to deployment, monitoring, and continuous improvement.
The role emphasizes building intelligent systems that can reason, plan, use tools, and make decisions, rather than standalone models or simple chatbots. You will apply modern Generative AI techniques and strong software engineering practices to deliver real-world AI outcomes on a scale.
Key Responsibilities
Experience needed: 5-7 years
Generative & Agentic AI Development
- Design and build LLM-based systems using:
- Retrieval Augmented Generation (RAG)
- Embeddings and vector search
- Prompt engineering and prompt optimization
- Function calling and tool usage
- Agentic and multi-agent workflows
- Develop AI systems that integrate LLMs with REST APIs, enterprise systems, data platforms, and workflows
- Apply LLM evaluation techniques to assess quality, reliability, safety, and performance
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End-to-End AI Engineering
- Own the full lifecycle of AI solutions—from prototype to production
- Build, deploy, and operate AI workloads in AWS environments
- Ensure production readiness with focus on scalability, reliability, performance, security, and cost optimization
- Implement CI/CD pipelines, automated testing, and versioning for AI systems
Engineering Excellence & Operations
- Apply strong software engineering and distributed systems principles to AI development
- Implement observability practices including logs, metrics, traces, and alerts
- Monitor model behavior, system health, latency, and failures in production
- Contribute to responsible AI practices, governance, and quality standards
Collaboration & Enablement
- Work closely with other AI engineers, data scientists, platform teams, and business stakeholders
- Contribute to building and scaling AI platforms and reusable components
- Support low-code / Copilot / Flow-style solutions where appropriate
- Share knowledge and mentor junior engineers on Generative and Agentic AI best practices
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Qualifications
Mandatory Technical Skills
Programming & Engineering
- Python
- REST APIs
- CI/CD pipelines
- Automated testing
- Distributed systems fundamentals
Generative & Agentic AI
- Generative AI concepts
- LLM-based systems
- Agentic and multi-agent workflows
- Retrieval Augmented Generation (RAG)
- Embeddings and vector databases
- Prompt engineering
- LLM evaluation
Cloud & AI Platforms
- AWS Bedrock
- Amazon SageMaker
Production & Operations
- Observability (logs, metrics, tracing, alerts)
- Monitoring and performance tuning
Nice to Have
- Experience supporting enterprise AI platforms or shared AI services
- Exposure to Copilot-style or workflow automation solutions
- Familiarity with Responsible AI principles and governance
- Experience working with cross-functional or client-facing teams
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