Live opening · Posted 1 day ago
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About the role
Description supplied by the original job listing.
The core responsibilities for the job include the following:
AI Application Development:
Design, build, and deploy AI-powered applications using large language models, multimodal models, and intelligent agents.
Develop scalable AI solutions that automate enterprise workflows and enhance customer experiences.
Build reusable AI services, APIs, and components that integrate seamlessly into the platform.
Rapidly prototype, validate, and productionize AI use cases across multiple industries.
LLM & Agent Engineering:
Develop advanced prompt engineering strategies, Retrieval-Augmented Generation (RAG) pipelines, and agentic workflows.
Build multi-agent systems capable of reasoning, planning, and executing complex enterprise tasks.
Integrate foundation models from leading providers while optimizing performance, reliability, and cost.
Evaluate, fine-tune, and optimize AI models for production use cases.
AI Platform Integration:
Integrate AI applications with enterprise systems, databases, APIs, and third-party platforms.
Build scalable inference pipelines and AI workflows that support production deployments.
Collaborate with platform and infrastructure teams to optimize model serving, orchestration, and deployment.
Implement robust evaluation frameworks to continuously measure AI quality and performance.
Performance & Reliability:
Optimize AI applications for latency, accuracy, scalability, and operational efficiency.
Implement observability, monitoring, logging, and evaluation pipelines for AI systems.
Ensure AI solutions meet enterprise requirements for security, privacy, governance, and compliance.
Troubleshoot production AI systems and continuously improve model performance through experimentation and feedback.
Engineering Excellence:
Write clean, maintainable, and production-quality code following engineering best practices.
Conduct code reviews and contribute to technical design discussions.
Collaborate closely with Product, Platform, Infrastructure, and Customer Success teams to deliver customer-centric AI solutions.
Stay current with emerging AI research, tools, and technologies, and evaluate their applicability to the platform.
Requirements:
3+ years of experience building AI, machine learning, or backend software applications.
Strong proficiency in Python with experience building production-grade applications.
Hands-on experience with large language models, prompt engineering, Retrieval-Augmented Generation (RAG), and AI agent frameworks.
Experience using frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, LangGraph, or similar.
Familiarity with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or PGVector.
Experience integrating AI applications with REST APIs, databases, and cloud services.
Understanding of model evaluation, prompt optimization, hallucination mitigation, and AI quality measurement.
Experience with Docker, Kubernetes, and cloud platforms such as AWS, Azure, or GCP.
Familiarity with Git, CI/CD pipelines, and software engineering best practices.
Understanding of distributed systems, scalable APIs, and enterprise application development.
Exposure to fine-tuning, model serving, MLOps, or inference infrastructure is highly desirable.
Bonus/Good to Have:
Generative AI: Experience building enterprise applications using GPT, Claude, Gemini, Llama, Mistral, or other foundation models.
AI Infrastructure: Experience with vLLM, TensorRT-LLM, TGI, model deployment, GPU optimization, or inference platforms.
Machine Learning: Experience with supervised learning, deep learning, model training, evaluation pipelines, and ML frameworks such as PyTorch or TensorFlow.
Enterprise Integrations: Experience integrating AI solutions with CRMs, ERPs, productivity tools, cloud platforms, and enterprise workflows.
Developer Platforms: Experience building SDKs, APIs, developer tools, or AI platform capabilities for external developers.
Preferred Attributes:
Founder-level ownership and bias for action.
Strong strategic thinking and ability to connect technical decisions to business impact.
Excellent communication and mentoring skills.
Thrives in ambiguity, fast-paced environments, and early-stage startup culture.
Skills
Generative AI, Machine Learning, Python, Prompt Engineering, LangChain, TensorFlow, PyTorch, LLMs, FastAPI, LangGraph
Experience
3-7 yrs
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