Senior Technical Lead – Generative AI

🕒 Ontem

🇮🇳 Índia – Remoto

💵 ₹3.000.000 - ₹5.000.000 / ano

⏰ Tempo Integral

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

👻 Score fantasma 20%

O que significa: quão provável esta vaga está aberta sem contratação ativa.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

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Weekday (YC W21)

SiteLinkedInTodas as Vagas

11 - 50 funcionários

Fundada em 2021

💼 Consultoria

👥 RH Tech

☁️ SaaS

Consulting • HR Tech • SaaS

A Weekday é uma plataforma moderna de recrutamento que combina tecnologias de IA com um vasto banco de dados de potenciais candidatos, com o objetivo de agilizar e simplificar o processo de contratação para empresas na Índia. A empresa oferece diversos serviços, incluindo uma abordagem proativa de outreach que ajuda empregadores a se conectarem com talentos de ponta, além de ferramentas para que candidatos se candidatem facilmente a vagas. O foco da Weekday em engajamento de candidatos por múltiplos canais — incluindo e-mail, WhatsApp e ligações telefônicas — a diferencia no competitivo mercado de agências de recrutamento.

Descrição

• Architect and develop Agentic AI and Generative AI systems from concept through production • Build multi-step reasoning agents, tool/function-calling workflows, and multi-agent architectures using LangGraph, AutoGen, CrewAI, or custom orchestration • Design and productionize scalable RAG pipelines, including chunking, embeddings, vector search, and hybrid retrieval • Evaluate and select foundation models based on performance, accuracy, latency, cost, and business requirements • Develop strategies for prompt engineering, model routing, fine-tuning, and optimization • Own technical architecture decisions for scalable, reliable, and cost-efficient LLM applications • Establish engineering standards covering testing, evaluation, observability, guardrails, hallucination mitigation, and production monitoring • Design APIs, microservices, and cloud-native architectures supporting AI applications at scale • Drive AI/LLMOps practices across model lifecycle management, deployment, monitoring, and continuous improvement • Lead, mentor, and develop AI/ML and backend engineers • Conduct technical design reviews, architecture discussions, and code reviews • Establish engineering best practices and promote high standards for production AI development • Provide technical direction while remaining actively involved in complex engineering problems • Partner with Product, Data Science, Platform, Security, and Compliance teams to deliver AI solutions aligned with business objectives • Ensure AI systems meet privacy, security, compliance, and responsible-AI requirements • Communicate complex technical concepts clearly to senior leadership and business stakeholders • Represent the AI engineering function in strategic discussions around GenAI technology and roadmap decisions

🎯 Requisitos

• 10+ years of overall software engineering experience, including 4+ years working directly with AI/ML systems • At least 2+ years of hands-on experience building and deploying LLM-based or agentic AI applications in production • Deep expertise in LLM application development, RAG, embeddings, vector databases, prompt engineering, and AI agents • Practical experience with multi-agent systems, tool/function calling, memory management, planning, and reasoning workflows • Strong Python and software engineering fundamentals with experience building scalable, distributed, production-grade systems • Experience with APIs, microservices, cloud-native architecture, and at least one major cloud platform such as AWS, Azure, or GCP • Hands-on experience with MLOps/LLMOps tools such as MLflow, LangSmith, Weights & Biases, or equivalent platforms • Working knowledge of LLM fine-tuning and evaluation techniques, including LoRA/PEFT, RLHF concepts, and offline/online evaluation frameworks • Proven ability to provide technical leadership, mentor engineers, own architecture decisions, and collaborate across teams • Strong communication skills with the ability to translate complex technical concepts into clear business and executive-level discussions • Experience deploying and fine-tuning open-source models such as Llama or Mistral, alongside proprietary models/APIs • Contributions to AI/GenAI open-source projects, technical publications, or conference presentations • Experience building AI solutions within regulated industries such as finance, healthcare, or telecom • Knowledge of AI guardrails, red-teaming, responsible AI, and model safety/evaluation frameworks • Previous formal people-management experience