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Job title: AI Engineer
Location: Remote (but have to be located in Bangalore, Hyderabad or Chennai)
Artificial General Intelligence (AGI) Data Services is at the forefront of AI innovation, specializing
in the development and refinement of large language models (LLMs). Our mission is to create AI
systems that can understand and generate high-quality code, revolutionizing the software
development landscape.
Job Description: As an LLM Evaluation Expert specializing in Coding, you will play a crucial role in
assessing and improving our language models coding capabilities. Your expertise will be
instrumental in evaluating LLM-generated code responses, making high-level judgments, and
setting the standard for what constitutes excellent AI-assisted coding.
Key Responsibilities:
• Critically analyze and evaluate code responses generated by our LLMs across various
programming languages and paradigms
• Exercise expert judgment to select the most appropriate and efficient code solutions from
multiple LLM-generated options
• Make informed decisions on behalf of our customers, ensuring that selected code meets
industry standards, best practices, and specific client needs
• Develop and write coding demonstrations to illustrate what good looks like in AI-generated
code, setting benchmarks for quality and efficiency
• Provide detailed feedback and explanations for your evaluations, helping to refine and
improve the LLM's understanding and output
• Collaborate with the AI research team to identify areas for improvement in the LLM's coding
capabilities
• Stay abreast of the latest developments in software engineering, coding standards, and AI to
ensure our evaluations remain cutting-edge
Required Qualifications:
• 3-5 years development experience using Python or Java.
• Advanced degree in Computer Science, Software Engineering, or a related field
• Extensive experience in software development across multiple programming
languages(Python, Java) and paradigms
• Demonstrated ability to critically evaluate code quality, efficiency, and adherence to best
practices
• Strong analytical and decision-making skills, with the ability to make complex judgments
under ambiguous circumstances
• Excellent written and verbal communication skills, with the ability to explain technical
concepts clearly
• Experience with Docker
• Experience in technical writing, particularly in creating coding examples or tutorials
Preferred Qualifications:
• Previous experience working with or evaluating AI systems, particularly in the context of code
generation
• Familiarity with a wide range of software development methodologies and architectural
patterns
• Understanding of machine learning concepts, particularly as they apply to natural language
processing and code generation
• Experience in creating or contributing to coding standards or style guides
This role requires a unique blend of technical expertise, critical thinking, and communication
skills. You will be the bridge between advanced AI technology and practical, real-world coding
applications. Your work will directly influence the development of next-generation AI coding
assistants, shaping the future of software development.
If you're passionate about code quality, have a keen eye for detail, and are excited about the
potential of AI in software engineering, we encourage you to apply for this pivotal role at AGI
Data Services.
Job ID: 148223873
Skills:
PostgreSQL, Celery, FastAPI, Python, LangChain, Phi-3, SLMs, Llama 3, Specialized LLMs, Vector DBs, Pinecone, Agentic Workflows, LangGraph, Mistral, Pydantic, Milvus, Advanced System Prompts, Real-time Market Data Feeds
Skills:
SQL Server, Datadog, Redis, Typescript, Docker, MongoDB, FastAPI, Python, Azure DevOps, OpenAI ecosystem, Generative AI, Prompt engineering, AI safety, Azure Application Insights, Azure OpenAI Services, OpenAI Agents SDK, Conversational AI, Multi-agent architectures
Skills:
Java, Gcp, Docker, Terraform, Ansible, Azure, Python, Kubernetes, AWS, CrewAI, LangChain, LLMs, Go, Pinecone, Semantic Kernel, AutoGen, FAISS, Weaviate
Skills:
Machine Learning, Deep Learning, Tensorflow, MLops, Pytorch, Python, Generative AI, Agentic AI architectures, AI ML development libraries, LLMOps, Scikit-learn, Model lifecycle management, RAG AI agents, Orchestration frameworks, Workflow automation, Prompt Engineering, Observability, Monitoring
Skills:
Java, Node.js, MongoDB, Sql, RAG Retrieval-Augmented Generation, Vector Search
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