Gen AI/ Agent Engineer

As a key member of our Gen AI team, you'll architect and develop AI-powered solutions that transform how our business operates. Your focus will be building intelligent agents that enhance sales, customer success, HR, finance, and other core functions.Pioneer next-generation enterprise applications by architecting scalable, interoperable AI agents that reimagine and automate workflows across sales, customer success, creative, finance and other core functions

Rapidly prototype and validate Gen AI solutions through quick proof-of-concepts, then leverage learnings and feedback to ship production-ready solutions at speed

Design robust systems that effectively manage uncertain AI-generated results, create reliable guardrails, and develop flexible products capable of handling the inherent variability in generative AI outputs.Treat prompt engineering as both an art and a science via iteration, analysis, and collaboration with cross-functional teams to translate human workflows into LLM instructions

Drive innovation by researching LLM and Generative AI advancements, sharing insights, and proposing new product initiatives that leverage emerging AI capabilities.Core Skills & Technologies:Strong programming skills: Proficiency in Python and/or JavaScript/TypeScriptDeep learning frameworks: Experience with PyTorch, TensorFlow, or JAXNLP understanding: Knowledge of language models, embeddings, and text processing techniques

Prompt engineering: Ability to craft effective prompts that generate desired outputs

Fine-tuning expertise: Experience fine-tuning foundation models for specific applications

Data engineering: Skills to prepare, clean, and structure data for AI training

System design: Capability to design scalable AI systems and workflows

Agent-Specific Skills:Agent architecture design: Understanding of different agent frameworks and architectures

Tool integration: Ability to connect agents with external tools, APIs, and data sources

Memory systems: Knowledge of techniques for implementing context and memory

Planning algorithms: Familiarity with goal-setting and planning approaches

Multi-agent systems: Experience designing systems where multiple agents collaborate

Feedback mechanisms: Implementation of human and automated feedback loops

Evaluation frameworks: Skills to assess agent performance and behavior

Specialized Knowledge:Reinforcement learning: Understanding of RLHF and related techniques

Retrieval-augmented generation (RAG): Experience implementing retrieval systems

Agentic workflows: Ability to create complex multi-step processing pipelines

Production deployment: Knowledge of containerization, APIs, and serving infrastructureLLMOps: Skills for monitoring, updating, and managing LLM applications in production

Vector databases: Experience with embedding storage and similarity search

Who You Are:Required total experience of 10 years.

Seasoned software engineer with proven experience building products 0-1 and a strong proficiency in Python. Push engineering boundaries by challenging traditional approaches and bringing proven expertise to adapt best practices for AI-first development. Have experience building autonomous Gen AI agents in sales, customer support, or other key functions, demonstrating proficiency in multi-agent systems and complex task decomposition.Have experience in developing and implementing evaluation frameworks for Gen AI products, including automated testing and human-in-the-loop feedback systems.

An experienced prompt engineer who has spent significant time optimizing Gen AI products through systematic experimentation and iteration. Gen AI enthusiast who deeply understands LLMs' capabilities and advocates for letting models shine rather than over-constraining them with deterministic prompting. Natural collaborator who communicates complex technical concepts clearly and works effectively with diverse stakeholders.