AI Engineer

Role & Responsibilities

Responsibilities

• Business: Immerse in operations until you think like an insider.

Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.

• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.

• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.

• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.

• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.

• Scale: Design complex multi-component systems end-to-end, evaluate architectural options for large initiatives across teams, guide technical decisions for your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.

• Documentation: Define documentation standards across teams in your area, create documentation systems and templates, train engineers on spec-driven development, and ensure documentation quality across projects. Lead pattern generalization initiatives, defining criteria for when to generalize versus keep custom.

• Reliability: Define reliability standards across teams in your area, drive post-incident improvements systematically, design capacity planning processes, andmentor engineers on SRE practices.

Ideal Candidate

• Strong Staff Software Engineer / FDE profile (full-stack + production GenAI, multi-team technical leadership)
• Mandatory (Experience 1) – Must have 7+ years of relevant professional software engineering experience, with demonstrated full-stack delivery across backend and frontend.
• Mandatory (Experience 2) – Must have deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.
• Mandatory (Experience 3) – Must have 2+ years of experience in generative AI applications developement — LLM integrations, vector databases, RAG systems, and evaluation pipelines
• Mandatory (Experience 4) – Must have strong experience with modern frontend frameworks (Next.js / React) and backend API development.
• Mandatory (Experience 5) – Must have extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).
• Mandatory (Experience 6) – Must have working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.
• Mandatory (Experience 7) – Must have strong experience with CI/CD pipelines (e.g. GitHub Actions), containerization, and production deployment strategies.
• Mandatory (Experience 8) – Must have demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them
• Preferred (Experience) – Advanced RAG techniques — hybrid search, reranking, query expansion — and establishing RAG standards across teams

Key Responsibilities

• Build and configure Copilot agents and agentic workflows in Copilot Studio
• Develop integrations using Power Platform, Azure Logic Apps, and REST/APIs
• Integrate Copilot with enterprise systems: Sharepoint, Outlook, Teams, Salesforce, TM1, etc.
• Implement data mapping, transformations, and workflow logic as per architecture
• Collaborate with solution architects to convert design instructions into working solutions
• Write scripts in PowerShell / Python / C# / JavaScript

Required Skills

• Strong hands-on experience with Agent implementation in Copilot Studio, Power Automate, Power Apps, Azure Logic Apps 
• Experience with M365, Dynamics, Azure services
• REST API integration, OAuth2, Azure AD (Entra ID) authentication
• Experience with at least two enterprise integrations: Sharepoint, Outlook, Teams, Salesforce, TM1
• Ability to understand technical diagrams, integration patterns, and solution specs

About Logikality

Logikality is building an AI-native mortgage intelligence platform for the U.S. mortgage industry. We are reimagining how mortgage operations are executed by combining AI, workflow automation, and domain expertise to solve one of the most document-intensive and decision-heavy industries in the world.

Our platform goes beyond document extraction. We are building AI systems that understand mortgage files, reason across multiple sources of information, identify risks and exceptions, support underwriting and quality control decisions, and continuously improve through expert feedback and rigorous evaluation.

Job Description

We are looking for a Generative AI Engineer to build and scale Logikality's AI-native mortgage platform.

The role requires strong hands-on engineering expertise in designing, building, and deploying production-grade Generative AI systems that power intelligent mortgage operations. You will work across LLM applications, AI agents, retrieval systems, reasoning workflows, backend services, APIs, and cloud infrastructure to transform complex mortgage workflows into reliable AI products.

This is a high-ownership role for someone who can rapidly convert business problems into scalable AI solutions with minimal supervision.

Key Requirements

• 3 to 8 years of experience in software engineering, AI engineering, or Generative AI development, preferably in startup environments. 
• B.E./B.Tech. in Computer Science or a related engineering discipline a premier engineering institution (e.g., IITs, IISc, NITs, BITS Pilani, or top-tier global universities).
• Proven experience independently owning projects end-to-end from solution design and model integration to production deployment, monitoring, and maintenance. 
• Strong proficiency in Python and modern backend development. 
• Hands-on experience building production-grade applications using Large Language Models (LLMs). 
• Experience with agentic AI frameworks, multi-agent workflows, function/tool calling, structured outputs, and prompt engineering. 
• Strong understanding of Retrieval-Augmented Generation (RAG), embeddings, vector databases, semantic search, and knowledge retrieval systems. 
• Experience integrating commercial and open-source foundation models (OpenAI, Anthropic, Gemini, Llama, Mistral, or similar). 
• Experience building AI pipelines using frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or equivalent orchestration frameworks. 
• Strong understanding of model evaluation, hallucination mitigation, guardrails, prompt optimisation, and LLM observability. 
• Experience with OCR, document intelligence, structured information extraction, or multimodal AI systems is preferred. 
• Strong knowledge of APIs, databases, cloud infrastructure, Docker, Kubernetes, and CI/CD pipelines. 
• Ability to design scalable, secure, and production-ready AI architectures. 
• Strong debugging skills, systems thinking, and an ownership mindset with the ability to move quickly in an early-stage startup. 

Preferred Experience

• Experience building AI copilots, autonomous agents, or enterprise AI assistants. 
• Familiarity with MCP, AI tool integration, and agent orchestration. 
• Experience fine-tuning, distillation, or evaluation of open-source LLMs. 
• Knowledge of AI safety, governance, and responsible AI practices. 
• Experience working with document-heavy enterprise domains such as financial services, banking, insurance, healthcare, legal, or mortgage technology. 
• Experience deploying AI applications on AWS, Azure, or GCP. 

What You'll Build

• AI agents that automate mortgage underwriting, quality control, compliance, and document review. 
• RAG-based knowledge systems that reason across large collections of mortgage documents. 
• Intelligent workflows combining LLM reasoning with deterministic business rules. 
• Production-grade AI APIs and backend services powering Logikality's platform. 
• Evaluation pipelines to continuously improve AI quality, accuracy, latency, and cost. 

Why Join Logikality?

At Logikality, you'll work on problems that require genuine reasoning, not just text generation. You'll help build AI systems that understand complex documents, synthesise information across workflows, explain decisions, identify exceptions, and improve through continuous learning and expert feedback.

This will be a full-time in-office role based in Bangalore. Immediate joiners are preferred.

Role: Full Stack GEN AI Engineer

Location: Remote - Bengaluru

Duration: Fulltime With VDart Digital

The role demands a developer who is not just familiar with Large Language Models (LLMs), but is an expert in building autonomous agentic workflows using the modern GenAI stack (LangChain, CrewAI, Vector DBs). Expertise in system design, cloud-native technologies, and CI/CD for AI-driven applications is essential for this high-impact delivery role.

Responsibilities

· Design, develop, and maintain full-stack applications that are scalable, robust, and meet the company's quality standards, with a specific focus on Generative AI integration.

· Agentic Orchestration: Build and deploy sophisticated multi-agent systems and autonomous workflows using frameworks like LangChain, CrewAI, or LangGraph.

· Collaborate effectively with cross-functional teams to define, design, and ship new features that bridge the gap between raw AI power and intuitive user workflows.

· Exhibit strong problem-solving skills with an emphasis on product development and driving architecture choices that enable a world-class user experience.

· Utilize a variety of modern web technologies and frameworks (React.js, Angular, or Vue.js) to build responsive and accessible user interfaces.

· Develop and maintain RESTful APIs and services with optimal performance and scalability, handling streaming AI responses and complex function-calling logic.

· Ensure code quality, organization, and automatization through best practices, including unit tests for prompts, model evaluation pipelines, and automated CI/CD for AI-driven features.

· Implement and optimize RAG (Retrieval-Augmented Generation) pipelines using Vector Databases and advanced retrieval techniques.

· Adapt to emerging technologies and frameworks, specifically new GenAI tools and frontier models, and apply them to operational and business needs.

· Manage individual project priorities, deadlines, and deliverables with minimal supervision.

Skill Requirements

· Excellent oral and written communication skills, with the ability to articulate complex AI and technical ideas to both technical and non-technical audiences.

· Profound knowledge of application development, data structures, networking, operating systems, and DBMS.

· Strong proficiency in backend programming languages for API development such as Python, Java, JavaScript (Node.js), or Go.

· Expertise in front-end technologies and frameworks such as React.js, Angular, or Vue.js.

· GenAI & Agentic Tools: Deep hands-on experience with LangChain, CrewAI, or AutoGen. Ability to manage agent memory, state, and tool-calling.

· In-depth understanding of SQL/NoSQL databases, data modeling, and experience with Vector Databases for RAG implementations.

· Solid grasp of system design, microservices architecture, and cloud-native technologies including Docker, Kubernetes, and GitHub Actions.

· Experience with distributed computing, machine learning frameworks, and tools, with a primary focus on Generative AI.

· Desirable (Good to Have): Experience with Generative or Adaptive UI development, where the interface dynamically adapts or renders components based on LLM outputs and real-time AI reasoning.

· A strong desire to learn and master new technologies and techniques in the rapidly evolving GenAI landscape.

Qualifications

· Bachelor’s degree in Computer Science, Engineering, or a related field.

· A minimum of 3-5 years of experience in full-stack development, with a proven track record of building and deploying Generative AI applications and agents.

· Portfolio of successfully deployed web applications and services, specifically showcasing AI agents, RAG implementations, or complex AI-driven features.

Key Responsibilities

• Build and configure Copilot agents and agentic workflows in Copilot Studio
• Develop integrations using Power Platform, Azure Logic Apps, and REST/APIs
• Integrate Copilot with enterprise systems: Sharepoint, Outlook, Teams, Salesforce, TM1, etc.
• Implement data mapping, transformations, and workflow logic as per architecture
• Collaborate with solution architects to convert design instructions into working solutions
• Write scripts in PowerShell / Python / C# / JavaScript

Required Skills

• Strong hands-on experience with Agent implementation in Copilot Studio, Power Automate, Power Apps, Azure Logic Apps 
• Experience with M365, Dynamics, Azure services
• REST API integration, OAuth2, Azure AD (Entra ID) authentication
• Experience with at least two enterprise integrations: Sharepoint, Outlook, Teams, Salesforce, TM1
• Ability to understand technical diagrams, integration patterns, and solution specs

About Marseer AI

Marseer AI (www.marseerai.com) is a Seattle-based company building an AI-powered marketing intelligence platform for DTC and retail e-commerce brands. The platform combines brand strategy, customer data, automation, and generative AI to help marketing teams drive consistent, data-driven engagement across email, SMS, paid media, SEO, and affiliate channels.

Role Overview

We are looking for an experienced AI Engineer - Full Stack Developer to join the Marseer platform team. This is a dual-track role: you will build and maintain AI agent pipelines, LLM integrations, and RAG-based intelligence systems on the backend, while also owning frontend interfaces that surface insights, recommendations, and campaign outputs to marketing teams and brand operators.

You should be equally comfortable designing multi-step agentic workflows in Python and building clean, responsive product interfaces in React/Next.js. You understand how LLMs behave in production, know how to engineer prompts and tool chains for reliability, and care deeply about the end-to-end user experience.

What You Will Do

- Design and implement multi-step AI agent workflows using LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar.

- Build and maintain RAG pipelines, including chunking strategies, embedding generation, vector store management, and retrieval tuning.

- Integrate with LLM providers such as OpenAI, Anthropic, or others, including prompt engineering, tool/function calling, structured output generation, and context window management.

- Develop AI-driven features such as campaign brief generation, audience recommendations, content variant creation, and performance insight summarization.

- Implement evaluation and observability frameworks to monitor LLM output quality, latency, and cost in production.

- Build frontend interfaces using React and Next.js, including dashboards, agent interaction UIs, campaign builders, and insight surfaces.

- Design and implement RESTful and/or GraphQL APIs in Python (FastAPI or Flask) or Node.js to serve AI outputs to the frontend.

- Integrate frontend with backend AI services, streaming LLM responses, and real-time status updates.

- Work with structured and unstructured marketing data, campaign performance metrics, audience segments, content libraries, and brand strategy documents.

- Integrate with marketing platforms and data sources such as Klaviyo, Google Ads, Meta, and Shopify.

Requirements

- 5-10 years of professional software engineering experience, with meaningful time in both backend and frontend development.

- Proven experience building and deploying LLM-powered applications in production, not just prototypes.

- Strong proficiency in Python for backend and AI development.

- Strong proficiency in React and Next.js for frontend development.

- Hands-on experience with LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or equivalent.

- Experience building RAG pipelines, vector stores such as Pinecone, Weaviate, pgvector, or similar, embedding models, and retrieval strategies.

- Experience with API design, REST or GraphQL, and backend service architecture.

Strongly Preferred

- Experience designing and building multi-agent or agentic AI systems with tool use, memory, and planning capabilities.

- Familiarity with prompt engineering best practices, structured output generation, and LLM evaluation methodologies.

- Experience with streaming LLM responses and real-time UI updates using SSE or WebSockets.

- Prior work in a SaaS product company shipping production features.

- Familiarity with marketing platforms, e-commerce data, or martech ecosystems.

Good to Have

- TypeScript and modern frontend tooling such as Tailwind CSS or shadcn/ui.

- Familiarity with Snowflake or other cloud data warehouses as data sources for AI pipelines.

- Experience with observability tools for LLM applications such as LangSmith, Helicone, Arize, or similar.

- Understanding of marketing concepts such as segmentation, campaign lifecycle, attribution, and content personalization.

What We Are Looking For

- Availability to work US business hours; overlap with US Eastern or Pacific timezone is required for client collaboration and team standups.

- Strong written and verbal English communication.

- Product sense and ownership mindset.

- Comfort with ambiguity in non-deterministic LLM-powered systems.

- Collaborative working style across engineering, design, and client-facing functions.

What We Offer

- Competitive compensation based on experience.

- Fully remote role; work from anywhere in India, with Hyderabad-based candidates preferred.

- High-impact work at the frontier of applied AI for marketing and e-commerce.

- Direct exposure to real brand problems, real data, and real production AI systems.

- A small, senior team where your architecture decisions matter and your contributions are visible.

Job Title: Senior Software Developer – Agentic AI / Backend

Location: Bangalore (Work from Office)

Experience: 5–8 Years

About the Role

We are looking for a highly skilled Software Developer to build next-generation agentic AI systems that automate and enhance customer support experiences. The role involves designing intelligent systems that can reason, retrieve knowledge, and perform automated actions by integrating with enterprise services and APIs.

Key Responsibilities

• Design and develop backend services using Node.js/TypeScript and Java (Spring Boot).
• Build scalable microservices and REST APIs that integrate with internal systems.
• Develop LLM-powered workflows, including RAG (Retrieval Augmented Generation) and AI agent capabilities.
• Implement workflow orchestration, session/context management, and automation logic.
• Integrate services with databases, APIs, and enterprise systems.
• Ensure scalability, security, monitoring, and reliability of production systems.
• Collaborate with cross-functional teams including Product, Data, and Engineering.
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Required Skills

• 5–8 years of backend development experience.
• Strong experience with Node.js/TypeScript and Java (Spring / Spring Boot).
• Experience building microservices, APIs, and distributed systems.
• Hands-on exposure to Generative AI, LLMs, or RAG-based systems.
• Good understanding of SQL/NoSQL databases.
• Familiarity with Docker, Kubernetes, CI/CD pipelines, and Git.
• Strong problem-solving and collaboration skills.
• 
  

Preferred Skills

• Experience with LangChain, OpenAI APIs, or similar LLM platforms.
• Exposure to AI agent architectures or automation frameworks.
• Knowledge of vector databases, embeddings, and semantic search.
• Experience working in large-scale production systems.

• Notice Period: Immediate to 30 days preferred.

We are looking for skilled AI Engineer for our organization. Please have a look to below details and revert accordingly if we can discuss further

Company Name: TechWize (A Business unit of Mangalam Information Technologies Pvt Ltd.)

Our Accreditations -

• 25 years of industry presence
• Salesforce Partner
• ISO 27001:2019 certified
• Great Place to Work certified
• HIPAA Compliant
• SOC2 Compliant
• NASSCOM Member

Our EVP (Employee Value proposition)

• We are a Great place to work certified company.
• 30 Earned Leaves during calendar Year
• Career progression and continuous Learning & Development (Technical, Soft skills, Communication, Leadership)
• Performance bonus & Loyalty Bonus Benefits
• 5 Days working
• Rewards and Recognition programs
• Standard Salary as per market norms
• Equal career opportunities, No discrimination
• Magnificent & Dynamic Culture
• Festival celebrations & fun events

Explore more : https://techwize.com/, https://mangalaminfotech.com/

Position: AI/Sr. AI Engineer

Job location: Ahmedabad

Experience: 4+ years

Job Overview:

We are seeking a highly experienced and innovative Senior AI Engineer with a strong background in Generative AI, including LLM fine-tuning and prompt engineering. This role requires hands-on expertise across NLP, Computer Vision, and AI agent-based systems, with the ability to build, deploy, and optimize scalable AI solutions using modern tools and frameworks.

Key Responsibilities:

• Design, fine-tune, and deploy generative AI models (LLMs, diffusion models, etc.) for real-world applications.
• Develop and maintain prompt engineering workflows, including prompt chaining, optimization, and evaluation for consistent output quality.
• Build NLP solutions for Q&A, summarization, information extraction, text classification, and more.
• Develop and integrate Computer Vision models for image processing, object detection, OCR, and multimodal tasks.
• Architect and implement AI agents using frameworks such as LangChain, AutoGen, CrewAI, or custom pipelines.
• Collaborate with cross-functional teams to gather requirements and deliver tailored AI-driven features.
• Optimize models for performance, cost-efficiency, and low latency in production.
• Continuously evaluate new AI research, tools, and frameworks and apply them where relevant.
• Mentor junior AI engineers and contribute to internal AI best practices and documentation.

Required Skills & Qualifications:

• Bachelor’s or Master’s in Computer Science, AI, Machine Learning, or related field.
• 5+ years of hands-on experience in AI/ML solution development.
• Proven expertise in fine-tuning LLMs (e.g., LLaMA, Mistral, Falcon, GPT-family) using techniques like LoRA, QLoRA, PEFT.
• Deep experience in prompt engineering, including zero-shot, few-shot, and retrieval-augmented generation (RAG).
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• Proficient in key AI libraries and frameworks:
• LLMs & GenAI: Hugging Face Transformers, LangChain, LlamaIndex, OpenAI API, Diffusers
• NLP: SpaCy, NLTK.
• Vision: OpenCV, MMDetection, YOLOv5/v8, Detectron2
• MLOps: MLflow, FastAPI, Docker, Git
• 
  
• Familiarity with vector databases (Pinecone, FAISS, Weaviate) and embedding generation.
• Experience with cloud platforms like AWS, GCP, or Azure, and deployment on in house GPU-backed infrastructure.
• Strong communication skills and ability to convert business problems into technical solutions.

You have experience in tackling organization wide challenges which are complex initiative that span multiple teams and products. Strong bias for operational and engineering excellence. critical that your voice is heard in product and business decisions. You like to find patterns that can reuse across multiple stacks, and willingness to help organisations adopt newer technologies. You are a great communicator and you take care setting high benchmarks in technical design choices. You spend a lot of time on research and love to discuss pros/cons of all choices and helping others towards making careful decisions.

Responsibilities:

• You will participate in all aspects of our development and provide expertise on architecture decisions we'll need to make to solve organisational problems.
• Driving technical roadmaps for the organisation.
• Set the north star for all key technical metrics to monitor and set high standards.
• Identify and articulate current state architecture and clarity on final state architecture and build organisation level influence to drive this to conclusion.
• Coaching / mentoring folks across the organisation on various technologies.
• Improve the recruiting and hiring process.
• Thinks about culture and how to impact it.
• Build, develop and scale our platform that powers real estate agents, buyers and sellers.
• Become a domain expert on real estate technology and products and an empathetic partner to our customers.
• Inspire, recruit and mentor your engineering colleagues.
• Operate in a scalable engineering culture that leverages modern principles of decoupled systems and automated CI/CD/testing/monitoring to drive. efficiencies.

Requirements:

• BS in CS or EE or equivalent.
• Proven track record working in top talent and high performance environments.
• Experience working on large scale systems in rapid growth environments.
• Experience with modern web frameworks (e. g. Go/React), distributed computing (e. g. Spark), public cloud platforms (e. g. AWS) and data pipelines
• Familiarity with containerisation, microservices architecture, continuous integration and delivery.
• Experience with multiple well-known products throughout their life cycles, from idea conception to product release and maintenance.
• 10+ years experience.

• Published Engineering blogs.
• Experience with multiple well-known products throughout their life cycles, from idea conception to product release and maintenance.
• External presentations in events.