Java NLP Engineer

🔹 Key Responsibilities

• Design, develop, and deploy production-grade AI/ML and Generative AI solutions

• Work on GEO, AEO, and SGE initiatives to improve visibility across AI-driven search platforms

• Optimize content and digital experiences for conversational queries and LLM-based search

• Develop solutions using LLMs, NLP, embeddings, semantic search, RAG, and vector databases

• Analyze search intent, AI-generated responses, citations, retrieval patterns, and content discoverability

• Build frameworks to measure GEO/AEO strategies and AI-search performance

• Collaborate with Product, Engineering, Content, SEO, Marketing, and Business teams

• Improve solution accuracy, relevance, latency, and user experience

🔹 Mandatory Requirements

✅ 1–4 years of professional experience

✅ Minimum 1 year of hands-on experience in GEO, AEO, or SGE

✅ Experience with prompt engineering, embeddings, vector search, or RAG systems

✅ Understanding of semantic search and entity-based optimization

✅ Exposure to ChatGPT, Google Gemini, or similar LLM platforms

✅ Knowledge of schema, context building, content structuring, and knowledge representation

🎓 Preferred Education

B.Tech, M.Tech, Integrated M.Sc., or MS from a Tier-1 engineering institute such as IIT, NIT, BITS, VIT, DTU, or NSUT.

This is a remote position.

About Leegality:

Leegality works with large Indian businesses to digitally transform critical compliance processes in a fast, easy and secure way.

We have multiple products across 2 categories:

Document Infrastructure:

Products that help businesses build paperless processes at scale:

1. Document Execution Workflow: A unified platform for businesses to digitally execute (eSign, eStamp, Template Pre-fill, Document Fraud Prevention etc.) agreements, forms and other documents in a compliant way. Currently in use by 2000+ Indian businesses from giants like HDFC and SBI Cards to high-growth disruptors like goDigit and Cars24.
2. Contract Management: An AI-powered platform for businesses to quickly review, negotiate and take action on contract
3. Signstation: A simple platform for businesses to digitally sign simple documents like invoices, policies and letters in a cost effective manner

Consent Infrastructure:

1. Consentin: An end-to-end DPDP and Privacy compliance platform for Indian businesses
2. Consentin Lens: A data discovery platform for businesses to identify the personal data they collect and store.

If you’re interested in building mission critical software that operates at population scale (75 million + Indians have signed at least one document through Leegality) then join Leegality.

Curious about our impact? Explore our customer success stories: leegality.com/case-studies

Our Culture

At Leegality, trust, ownership, transparency, and having fun while doing meaningful work are core to how we operate — not just values on paper. Our team rated us an incredible 97 eNPS for FY 2023–24 — the highest among 175+ startups surveyed.

We focus deeply on helping our people grow and stay motivated. Some of the perks you’ll enjoy:

• Flexible working hours
• Hybrid work setup
• Bi-annual performance appraisals
• A culture that rewards initiative, curiosity, and impact

If you're looking for a place where you can make a real difference while working with smart, driven, and genuinely nice people, welcome to Leegality.

Location: Hybrid

Job Brief:

• As a Machine Learning Engineer specializing in Computer Vision (CV) and Natural Language Processing (NLP), you will develop solutions to interesting technical problems, exploring exciting growth opportunities and having a real impact on our product, particularly focusing on document and content intelligence.
• To ensure success, you should demonstrate solid data science knowledge and experience in a related ML, CV, or NLP role. A first-class engineer will be someone whose expertise enhances our systems for document intelligence and content processing

Responsibilities:

• Designing machine learning systems, self-running artificial intelligence (AI) software, and specialized models for Computer Vision and Natural Language Processing applications.
• Transforming data science prototypes and applying appropriate deep learning algorithms and tools to text and image/document data.
• Solving complex CV and NLP problems with multi-layered data types, such as image/document classification, information extraction, semantic search, and object detection.
• Optimizing existing machine learning models, with a focus on high-performance model deployment for CV and NLP tasks.
• Developing ML algorithms (including large language models/LLMs and computer vision models) to analyze huge volumes of historical text, image, and document data to make predictions and automate workflows.
• Running tests, performing statistical analysis, and interpreting test results for CV/NLP model performance.
• Documenting machine learning processes, model architectures, and data pipelines.
• Keeping abreast of developments in machine learning, Computer Vision, and Natural Language Processing.

Requirements:

• 3+ years of relevant experience in Machine Learning Engineering, with a strong focus on Computer Vision and/or Natural Language Processing.
• Advanced proficiency with Python.
• Extensive knowledge of ML frameworks, libraries (e.g., PyTorch, Transformers), data structures, data modeling, and software architecture.
• Experience with building and maintaining scalable RESTful APIs (e.g., FastAPI).
• In-depth knowledge of mathematics, statistics, deep learning (CNNs, RNNs, Transformers), and algorithms.
• Superb analytical and problem-solving abilities, especially for unstructured data challenges.
• Great communication and collaboration skills.
• Excellent time management and organizational abilities.
• Experience with cloud platforms (e.g., AWS) for model deployment and MLOps.

Recruitment Process:

• Our hiring process combines AI-powered evaluations with structured interviews to ensure a fair and seamless experience.
• You will be contacted via email with the next steps upon being shortlisted.
• The process may include Assessments, AI-enabled interviews, and In-Person Interviews with our team.
• Final selection and CTC will be based on your overall performance and experience.

Apply directly through our career page: https://careers.leegality.com/jobs/Careers

For more information about us please visit our:

Our Company and Culture: https://bit.ly/3Iqm5SB

Our Website: www.leegality.com/

Our LinkedIn Page: www.linkedin.com/company/leegality/

Leegality's Privacy Notice: https://www.leegality.com/employee-privacy-notice

Job Description: Senior Java/Python Developer (AI & GenAI Specialist)

Location

Position Summary

We are seeking an experienced Senior Java/Python Developer with strong expertise in enterprise application development and extensive hands-on experience in Artificial Intelligence (AI), Generative AI (GenAI), Large Language Models (LLMs), and AI-powered application development. The ideal candidate will lead the design, development, and deployment of scalable, intelligent solutions that integrate modern AI technologies with enterprise-grade Java and Python ecosystems.

This role requires a combination of strong software engineering skills, AI innovation capabilities, and architectural leadership.

Key Responsibilities

• Application Development

• Design, develop, and maintain scalable enterprise applications using Java and Python.

• Develop RESTful APIs, microservices, and event-driven architectures.

• Build high-performance backend systems using Spring Boot, FastAPI, Flask, or Django.

• Ensure code quality through unit testing, integration testing, and code reviews.

AI & Generative AI Development

• Design and implement AI-powered solutions leveraging Large Language Models (LLMs).

• Develop intelligent applications using OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, and similar platforms.

• Build Retrieval Augmented Generation (RAG) architectures for enterprise knowledge systems.

• Implement AI agents, copilots, chatbots, virtual assistants, and workflow automation solutions.

• Engineer prompts and build prompt orchestration frameworks.

• Develop multi-agent AI systems and autonomous AI workflows.

Required Technical Skills

Core Programming

• Expert-level proficiency in:

o Java (Java 11/17/21)

o Python 3.x

• Strong understanding of OOP, design patterns, and software engineering principles.

Java Technologies

• Spring Boot

• Spring Cloud

• Hibernate/JPA

• Microservices Architecture

• Kafka/RabbitMQ

• REST API Development

Python Technologies

• FastAPI

• Flask

• Django

• Pandas

• NumPy

• Async Programming

Generative AI & LLMs

• OpenAI APIs

• Azure OpenAI

• LangChain

• LangGraph

• LlamaIndex

• Semantic Kernel

• Hugging Face

• Prompt Engineering

• RAG Frameworks

• AI Agent Frameworks

• Vector Databases (Pinecone, Weaviate, ChromaDB, Milvus, FAISS)

Preferred Qualifications

• Experience developing enterprise AI copilots and intelligent assistants.

• Experience implementing AI solutions using Microsoft Copilot Studio, Azure AI Services, or similar platforms.

• Knowledge of AI governance, responsible AI, security, and compliance frameworks.

• Experience in travel, finance, telecom, retail, or large enterprise environments.

• Exposure to graph databases and knowledge graphs.

• Understanding of multimodal AI (text, image, audio, video).

Educational Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or related discipline.

• Generative AI certifications preferred.

Key Competencies

• Solution Architecture

• AI Innovation & Thought Leadership

• Problem Solving

• Stakeholder Management

• Technical Mentoring

• Agile Development

• Analytical Thinking

• Communication & Presentation Skills

Success Metrics

• Delivery of scalable AI-enabled enterprise solutions.

• Reduction in operational effort through AI automation.

• Successful deployment of GenAI applications into production.

• Application performance, reliability, and security.

• Adoption of AI best practices across development teams.

Roles & Responsibilities

• Design and develop intelligent AI-based applications using advanced NLP and LLM techniques to solve real-world business challenges in financial services.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging structured and unstructured financial data.
• Integrate and orchestrate LLMs/SLMs for question-answering, summarization, semantic search, and document understanding.
• Develop and maintain RESTful APIs (sync and async) to serve NLP models and chatbot interfaces using frameworks like FastAPI, Flask, etc.
• Should have knowledge of advanced prompting techniques.
• Implement semantic search, hybrid search, and text retrieval systems using Elasticsearch and vector databases (e.g., FAISS, Pinecone, Weaviate).
• Perform NLP tasks such as entity recognition, text classification, intent detection, embedding generation, and sentiment analysis where required.
• Monitor and fine-tune LLM/SLM performance with real-world user data to improve relevance, latency, and accuracy.
• Exposure to LLMOps tools for monitoring, evaluation, and versioning of AI models in production.
• Build, train, and evaluate deep learning models for NLP tasks including classification, NER, summarization, and embedding generation.
• Develop traditional machine learning models (e.g., regression, decision trees, clustering) for structured data analysis and prediction tasks.
• Interact with cross-functional teams to understand system issues and follow up with respective teams to get them fixed.
• Understand and identify areas of improvement across businesses and participate in solution identification and implementation.
• Should be able to work as an Individual Contributor on new and existing projects.
• Positive and problem-solving attitude, must work as an independent contributor.

Ideal Candidate

1.Strong Data Scientist / AI Engineer / Generative AI Engineer profile.

2.Mandatory (Experience 1) - Must have 3+ years of hands-on experience in Data Science, Artificial Intelligence, Machine Learning, Deep Learning, NLP, or Generative AI application development.

3.Mandatory (Experience 2) - Must have strong hands-on experience in Python programming, backend development, API development, and production-grade application support

4.Mandatory (Experience 3) - Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, or Scikit-learn.

5.Mandatory (Experience 4) - Must have hands-on experience in NLP use cases such as text classification, sentiment analysis, entity recognition (NER), semantic search, embeddings, or document understanding.

6.Mandatory (Experience 5) - Must have experience working with Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Phi, Claude, Gemini, or similar models

.7.Mandatory (Experience 6) - Must have hands-on experience building or implementing Retrieval Augmented Generation (RAG) solutions, vector search, semantic search, or knowledge-based AI applications.

8.Mandatory (Experience 7) - Must have experience with Prompt Engineering and Generative AI frameworks such as LangChain, LangGraph, AI Agents, Azure OpenAI, or similar technologies.

9.Mandatory (Experience 8) - Must have experience developing, consuming, or integrating APIs using Python frameworks such as FastAPI, Flask, or similar technologies.

10.Mandatory (CTC) - The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

11.Preferred (Experience 1) - Experience with LLMOps/MLOps tools for monitoring, evaluation, experimentation, and versioning of AI models.

12.Preferred (Experience 2) - Exposure to Azure OpenAI, Azure Kubernetes Service (AKS), Kubernetes, cloud-native AI deployments, or distributed systems.

13.Preferred (Experience 3) - Experience working with PostgreSQL, MongoDB, Redis, Kafka, or large-scale data platforms.

14.Preferred (Experience 4) - Familiarity with Docker, Kubernetes, cloud platforms, and scalable deployment architecture.

15.Preferred (Company) - Candidates from AI-first startups, product companies, SaaS organizations, fintech, or data-driven technology companies.

16.Mandatory ( Age ) - Candidate Should be Below 28 Years.

17.Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.

Role: Developer – Java GenAI

Location: Hyderabad / Bangalore

Work Mode: Hybrid

Experience: Relevant experience in Java, GenAI and Microservices

Notice Period: Immediate to 15th October Joiners

Key Skills: Java, Spring Boot, Microservices, Kafka, LLM, RAG, Vector Databases, LangChain/LangGraph, Spring AI, PL/SQL, GCP/AWS, JMS, DevOps, CI/CD, JUnit, Mockito, Oracle/RDBMS, Redis/NoSQL.

Good to Have: Azure, Docker, Kubernetes/PaaS, Python, GitHub Copilot.

Strong understanding of Agile/Scrum with excellent communication, teamwork, organization and problem-solving skills.

Job Description: Senior Full Stack AI Engineer 

Position: Senior Full Stack AI Engineer ​

Experience: 6+ Years​

Location: Bangalore (preferred), Hyderabad​

Joining: Immediate 

About the Role 

We are looking for highly skilled Senior Full Stack AI Engineers who can independently 

design, build, and deploy AI-powered applications leveraging Large Language Models 

(LLMs). The ideal candidate should be equally comfortable working across the full stack, 

from developing scalable backend services and modern frontend applications to creating AI-

driven solutions and automated testing frameworks that enable developer-led quality 

engineering. 

This role requires hands-on expertise in LLM development, application architecture, and test 

automation, effectively helping organizations accelerate delivery while reducing dependency 

on traditional QA teams. 

Key Responsibilities 

∙Design, develop, and deploy AI-powered applications using Large Language Models 

(LLMs), with experience in Claude preferred. 

∙Architect and build scalable full stack applications using Java, Spring Boot, 

ReactJS, NextJS, TypeScript, and JavaScript. 

∙Develop intelligent workflows utilizing AI agents, prompt engineering, retrieval-

augmented generation (RAG), and model integrations. 

∙Create end-to-end automated test suites using Playwright, Perfecto, and other 

modern automation frameworks to support developer-led testing. 

∙Build and integrate RESTful APIs and microservices following modern architecture 

principles. 

∙Design and manage data solutions using SQL, NoSQL, and MongoDB. 

∙Develop event-driven applications using messaging platforms such as Kafka. 

∙Implement secure, scalable, and high-performance solutions using Spring Security, 

OAuth, and multi-threaded programming. 

∙Leverage AWS services including ECS, Lambda, and Step Functions to build cloud-

Strong Backend Software Engineer Profile with strong Core Java expertise

2

Mandatory (Experience 1): Must have 2+ years of hands-on backend software engineering experience.

3

Mandatory (Experience 2): Must be able to design and implement moderately complex features with minimal supervision, and contribute to system design and architecture discussions.

4

Mandatory (Experience 3): Must be comfortable owning business-critical production components — maintaining connectors, handling customer escalations, security fixes, bug fixes, and building new features end-to-end.

5

Mandatory (Tech skill 1): Must have strong, current Core Java depth with solid, clear coding fundamentals — Java is the primary skill for this role. Deep hands-on core engineering strength matters more than framework knowledge.

6

Mandatory (Tech skill 2): Must have strong core backend engineering fundamentals and experience with scalable systems (connectors handle millions of events/data points daily across customers).

7

Mandatory (Tech skill 3): Must have microservices experience.

8

Mandatory (AI Fluency): Must have demonstrated, hands-on use of AI coding assistants (Claude, GitHub Copilot, Cursor, etc.) as a core part of the daily workflow — scaffolding, writing tests, reviewing code, and debugging — with the ability to write precise, effective prompts for production-quality output, decompose tasks so AI assistance is effective, and critically evaluate AI-generated code for correctness, security, and standards before merging.

9

Mandatory (AI-Native): Must have actually built and deployed AI/LLM-powered features in production (e.g. RAG, LLM-based scoring, AI assistant) — demonstrable AI-native engineering, not merely using AI tools to write code.

10

Mandatory (Database): Hands-on database / JDBC integration experience in a production environment.

11

Mandatory (Company): Must come from a product company background (B2B SaaS or B2C both acceptable).

12

Mandatory (Note1): This is a 3-month contract role. Candidate must be comfortable with the contract engagement and able to join immediately (urgent — onboarding within ~a week)

13

Mandatory (Note 2): Must be based in or near Chennai, Bangalore, or Ahmedabad (Chennai: hybrid, Tue & Thu in office)

14

Preferred (Backend): Hands-on Python experience is a plus.

Strong Backend Software Engineer Profile with strong Core Java expertise

2

Mandatory (Experience 1): Must have 2+ years of hands-on backend software engineering experience.

3

Mandatory (Experience 2): Must be able to design and implement moderately complex features with minimal supervision, and contribute to system design and architecture discussions.

4

Mandatory (Experience 3): Must be comfortable owning business-critical production components — maintaining connectors, handling customer escalations, security fixes, bug fixes, and building new features end-to-end.

5

Mandatory (Tech skill 1): Must have strong, current Core Java depth with solid, clear coding fundamentals — Java is the primary skill for this role. Deep hands-on core engineering strength matters more than framework knowledge.

6

Mandatory (Tech skill 2): Must have strong core backend engineering fundamentals and experience with scalable systems (connectors handle millions of events/data points daily across customers).

7

Mandatory (Tech skill 3): Must have microservices experience.

8

Mandatory (AI Fluency): Must have demonstrated, hands-on use of AI coding assistants (Claude, GitHub Copilot, Cursor, etc.) as a core part of the daily workflow — scaffolding, writing tests, reviewing code, and debugging — with the ability to write precise, effective prompts for production-quality output, decompose tasks so AI assistance is effective, and critically evaluate AI-generated code for correctness, security, and standards before merging.

9

Mandatory (AI-Native): Must have actually built and deployed AI/LLM-powered features in production (e.g. RAG, LLM-based scoring, AI assistant) — demonstrable AI-native engineering, not merely using AI tools to write code.

10

Mandatory (Database): Hands-on database / JDBC integration experience in a production environment.

11

Mandatory (Company): Must come from a product company background (B2B SaaS or B2C both acceptable).

12

Mandatory (Note1): This is a 3-month contract role. Candidate must be comfortable with the contract engagement and able to join immediately (urgent — onboarding within ~a week)

13

Mandatory (Note 2): Must be based in or near Chennai, Bangalore, or Ahmedabad (Chennai: hybrid, Tue & Thu in office)

14

Preferred (Backend): Hands-on Python experience is a plus.

Location -Bangalore

Work Mode -Fully in-office, 6 days a week

Experience -3+ years in AI engineering, with LLM-based systems shipped to production

About the Role

● The AI Engineer will own systems that read, search and reason over project and tender documents.

● Inputs include large tender packages, scanned PDFs, BOQs, tables, forms and engineering drawings such as P&IDs.; Outputs should include accurate answers with source references, structured data and workflows used by estimators and project teams in live bids, planning, procurement and execution.

● The role covers taking features from initial experiments to production and owning their accuracy, latency and cost after release.

Key Responsibilities

Agents and Retrieval

● Build AI agents that plan and execute multi-step tasks using document search, tools and APIs.

● Build RAG pipelines covering ingestion, retrieval, reranking and answers with source references.

● Use agent workflows within retrieval to refine searches, collect supporting evidence and verify outputs.

Document Intelligence

● Build extraction pipelines for PDFs, scanned documents, tables and forms.

● Convert unstructured tender content into structured data that the platform can use.

Vision and Image Understanding

● Build image-understanding workflows for P&IDs;, including symbols, equipment, labels and connections.

● Locate and remove selected elements from diagram images while preserving surrounding content.

Quality and Reliability

● Create evaluation datasets and automated checks to measure accuracy and catch regressions.

● Debug failures across retrieval, agent decisions, tool calls and model outputs.

Product and Production

● Build backend services and REST APIs. ● Integrate AI features into the Workwise web application.

● Take features from experiment to production while managing reliability, latency and cost

Required Qualifications

● 3+ years of hands-on experience building AI systems, including at least one LLM-based application running in production.

● Strong Python and software engineering fundamentals.

● Experience with backend services, REST APIs, databases, authentication and frontend integration.

● Experience building applications using LLM APIs.

● Working knowledge of RAG, embeddings, retrieval and vector databases.

● Experience with tool calling, structured outputs and multi-step agent workflows.

● Working understanding of multimodal models and image processing for visual analysis and editing.

● Systematic evaluation skills: measuring results and investigating system failures.

● Ownership of implementation, testing, deployment and ongoing improvement.

Good to Have

● OCR, document layout analysis or complex table extraction.

● Computer vision experience, including object detection, segmentation or image inpainting.

● Familiarity with construction, procurement or tender documents.

● Cloud infrastructure and production monitoring.

● Working knowledge of Go. 

About Us

We're building the next generation of AI-powered business software. Our Chatbot application brings AI directly into customer and business workflows, combining a robust backend with LLM-powered agents to get real work done through conversation.

This is a chance to work on hard problems in backend systems, LLM agents, and orchestration — building zero-to-one, owning your area end-to-end, and shipping to production at scale.

Note: This is a customer-facing role, and strong communication skills are essential.

About the Role

We're looking for a Lead Software Engineer to help build and scale the backend and AI capabilities of our Chatbot application. This is a backend-heavy role for someone who can design robust, production-grade systems in Java while also bringing hands-on experience building LLM agents and orchestration layers that power intelligent conversational experiences.

What You'll Do

• Design, build, and scale backend services in Java that power the Chatbot application
• Build and integrate LLM-powered agents into the chatbot, including agent orchestration, tool use, and multi-step reasoning workflows
• Own features end-to-end — from architecture and design through implementation, testing, deployment, and iteration
• Drive technical decisions on system architecture, reliability, performance, and scalability for a backend serving real-time conversational workloads
• Lead by example — set engineering standards, review designs and code, and mentor engineers on the team
• Collaborate closely with product, design, and AI/ML teams to translate business requirements into shipped functionality
• Work directly with customers to understand real-world use cases, troubleshoot issues, and gather feedback to inform the roadmap
• Continuously improve the chatbot's conversational quality, reliability, and response accuracy

What We're Looking For

• 4–6 years of backend engineering experience, with strong, hands-on expertise in Java
• Practical experience building LLM-powered agents and agent orchestration in production systems
• Solid understanding of LLM fundamentals — prompting, tool use, reasoning, and evaluation
• Strong experience designing and building scalable, production-grade backend systems and APIs
• Ability to take technical ownership and lead design/architecture decisions with minimal oversight
• Comfort working in a fast-moving, high-ownership environment, balancing hands-on coding with technical leadership
• Excellent communication skills — this is a customer-facing role, and you'll regularly engage directly with customers to understand needs and explain technical solutions