Weekday AI

Proactive software engineer recruitment via referrals

Agentic AI Engineer

AI Application EngineeringConfirmed live in the last 24 hours

Full-timeRemote in IndiaNo salary listedRemote

About the Job

Requirements

At least 6 years of experience in traditional machine learning, including at least 2 years of hands-on Generative AI experience.
Strong experience with large language models, prompt engineering, and agentic systems.
Real-world experience with LangChain, LangGraph, or similar agentic frameworks.
Strong Python skills for API wrappers, third-party integrations, and internal tooling.
A solid foundation in Transformers, convolutional neural networks, and recurrent neural networks, with hands-on experience using TensorFlow, PyTorch, and Scikit-learn.
Experience with natural language processing, embedding models, and vector databases.
Hands-on experience with OpenAI, Llama or Llama 2, Azure OpenAI, and other open-source models.
Experience designing distributed, cloud-native architectures, including microservices and REST APIs.
Proficiency with AWS, Azure, or GCP, plus Docker and Kubernetes.
MLOps or LLMOps experience covering training, deployment, monitoring, and lifecycle management.
Excellent communication skills, including translating technical concepts for non-technical stakeholders.
A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related field.
Comfort working at a startup pace and a strong ownership mentality.

Responsibilities

Architect and build scalable Generative AI and agentic AI applications end to end.
Design LLM-powered workflows and prompt strategies for reflexive, self-learning, multi-agent systems.
Build intelligent AI agents using LangChain and LangGraph for use cases such as natural-language-to-SQL, autonomous task agents, and retrieval-augmented generation pipelines.
Select, customize, fine-tune, and optimize state-of-the-art large language models.
Design and own full machine-learning and Generative AI pipelines, including training, deployment, monitoring, and lifecycle management.
Build APIs, microservices, and integration frameworks to bring AI into enterprise products.
Promote responsible AI practices by mitigating hallucinations, bias, and reliability risks.
Partner with customers, product, and engineering teams to translate business needs into robust AI architecture.
Mentor engineers and help shape the long-term AI platform strategy.

Desired Qualifications

Experience fine-tuning large language models using LoRA, RLHF, or PEFT.
Experience with performance optimization, including GPU or TPU acceleration, quantization, pruning, or distillation.
Experience with AI observability or monitoring tools.
Familiarity with AI governance and compliance, including GDPR and SOC 2.
Prior consulting or solution-architecture experience shipping enterprise AI products.
Background in financial services, healthcare, or insurance.

Agentic AI Engineer

Weekday AI · India (Remote) · Full-time · Posted 2026-09-11

Workplace: remote

Department: Weekday's Client via platform

Description

This role is for one of Weekday’s clients

Min Experience: 5+ years
Location: Remote (India)
JobType: full-time

We're looking for a Senior Agentic AI/Generative AI Engineer to help architect our next-generation AI-driven products — from prototyping through production deployment. This is a customer-facing role where you'll move fluidly between solution architecture, hands-on engineering, and client conversations.

Requirements

Key Responsibilities:

Architect and build scalable Generative AI and agentic AI applications, end to end
Design LLM-powered workflows and prompt strategies for reflexive, self-learning, multi-agent systems
Build intelligent AI agents using LangChain and LangGraph for use cases like NL-to-SQL, autonomous task agents, and RAG pipelines
Select, customize, fine-tune, and optimize state-of-the-art LLMs
Design and own full ML/GenAI pipelines — training, deployment, monitoring, lifecycle management
Build APIs, microservices, and integration frameworks to bring AI into enterprise products
Champion responsible AI practices — mitigating hallucinations, bias, and reliability risks
Partner directly with customers, product, and engineering to turn business needs into robust AI architecture
Mentor engineers and help shape our long-term AI platform strategy

Required Qualifications:

6+ years in traditional ML, including 2+ years hands-on with Generative AI
Strong experience with LLMs (GPT and similar), prompt engineering, and agentic systems
Real-world experience with LangChain/LangGraph or similar agentic frameworks
Strong Python skills — API wrappers, third-party integrations, internal tooling
Solid foundation in Transformers, CNNs, RNNs — hands-on with TensorFlow, PyTorch, Scikit-learn
Experience with NLP, embedding models, and vector databases
Hands-on work with OpenAI, Llama/Llama2, Azure OpenAI, and other open-source models
Experience designing distributed, cloud-native architectures (microservices, REST APIs)
Proficiency with AWS, Azure, or GCP, plus Docker/Kubernetes
MLOps/LLMOps experience — training, deployment, monitoring, lifecycle management
Excellent communication skills — you can translate technical depth for non-technical stakeholders
Bachelor's or Master's in CS, Data Science, Engineering, Math, Statistics, or related field
Comfort with startup pace and strong ownership mentality

Preferred Qualifications:

LLM fine-tuning experience (LoRA, RLHF, PEFT)
Performance optimization (GPU/TPU acceleration, quantization, pruning, distillation)
AI observability/monitoring tool experience
Familiarity with AI governance and compliance (GDPR, SOC 2)
Prior consulting or solution-architecture experience shipping enterprise AI products
Background in financial services, healthcare, or insurance

Must-have skills

Agentic AI, Generative AI, Artificial Intelligence

Good-to-have skills

Machine Learning, LangChain, LangGraph

Apply

Apply at Weekday AI

About the Company

Weekday AI

Proactive software engineer recruitment via referrals

Weekday.works helps companies hire software engineers through proactive outreach and peer-recommended candidates. Its platform automates tracking, pipeline management, and provides weekly updates, while it actively identifies engineers via peer networks, reaches out, shortlists, checks references, and schedules interviews. Differentiators include peer-backed vetting instead of traditional job boards, proactive outreach, and a passive-income reference feature that monetizes referrals. The goal is to reduce the time and effort of hiring by connecting companies with pre-vetted engineers who are open to new opportunities through a network-driven approach.

Company size: 201-500
Company stage: Seed
Total funding: $2.3M
Headquarters: Bengaluru, India
Founded: 2021

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