Job Summary
This role would build intelligent systems that not only generate novel content and data but also exhibit autonomous decision-making and action-taking capabilities. This role requires a strong foundation in software engineering principles to effectively develop, integrate, and deploy these advanced AI solutions. By leveraging large language models and other generative techniques to create sophisticated AI agents capable of independent problem-solving and goal achievement, this role will be instrumental in developing cutting‑edge intelligent applications that will significantly enhance our operational efficiency and create novel product features.
Essential Responsibilities
Designing, developing, and deploying generative AI models (e.g., LLMs, diffusion models)
Architecting and building agentic systems with autonomous decision‑making capabilities
Integrating generative AI and agentic solutions into existing products and services
Developing and maintaining the software infrastructure required for AI/ML pipeline
Developing and implementing data pipelines for training and evaluating AI models
Collaboration, Documentation, Monitoring & Evaluation of AI Systems
Conducting research and experimentation with new generative AI and agentic techniques
Other duties as assigned or requested
Experience
Required
5 years' experience in Software Development experience (Python preferred)
3 years' experience working with large language models (LLMs)
3 years' experience in Building and deploying AI agent systems or similar autonomous systems
2 years' experience in Developing and deploying machine learning models in production
Preferred
2 years' Familiarity with Cloud Computing Platforms
1 year experience working with specific Agentic Frameworks (like LangChain, AutoGPT,Semantic Kernel, etc.)
1 year experience in Deploying AI models at scale in high‑throughput, low‑latency environments
Skills
Proficient in Python and relevant AI/ML libraries
Significant experience in prompt engineering and fine tuning LLM models
Knowledge and experience in different generative AI techniques and their applications
Ability to design and implement agentic frameworks and architectures
Knowledge of techniques for grounding generative models with external knowledge sources (e.g., retrieval‑augmented generation, Knowledge graphs)
Familiarity with MLOps principles and tools for model deployment and monitoring
Understanding of the security implications and mitigation strategies for generative AI and agentic systems
Ability to stay up‑to‑date with the latest advancements in AI and generative models
Strong problem‑solving and analytical skills
Excellent communication and collaboration skills
Education
Required
Bachelor’s degree in Computer Science, Information Science, Artificial Intelligence, Data Science or similar degrees.
Preferred
Master's degree in Computer Science, Information Science, Artificial Intelligence, Data Science or similar degrees
Licenses or Certifications
Required
None
Preferred
Google Cloud Professional Machine Learning Engineer
Travel Required: Less than 25%
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