AI Solutions Engineer (GenAI & Full Stack),

Company: Wissen Technology

Position: Python AI Engineer

Experience: 4-6 Years

Location: Bengaluru

Employment Type: Full-time

About Wissen Technology

Wissen Technology is a global technology services company focused on delivering innovative software engineering, data, and technology solutions to leading enterprises. The company works with clients across industries to build scalable, high-performance technology platforms and solve complex business and technology challenges.

With a strong focus on engineering excellence, innovation, and collaboration, Wissen Technology brings together skilled technology professionals across areas such as software engineering, data engineering, cloud, analytics, and digital transformation.

At Wissen Technology, employees have the opportunity to work on challenging technology projects, collaborate with experienced engineering teams, and contribute to solutions that create measurable business impact.

Job Summary

Wissen Technology is hiring a Python AI Engineer for a team building a finance application in global financial services. You will use Python to build LLM-powered applications and AI agents that help finance and operations users find, understand, and act on their data. The ideal candidate should have strong expertise in Core Python, data handling, and AI/LLM engineering and hands-on experience in developing AI-powered applications using Agentic AI frameworks such as LangChain and LangGraph, along with Retrieval-Augmented Generation (RAG).

Job Responsibilities:

• Develop and maintain applications using Core Python.
• Design and develop scalable backend services using FastAPI.
• Build and integrate RESTful APIs for application development.
• Work with NumPy and Pandas for data manipulation and processing.
• Develop AI-powered applications using Generative AI and LLM technologies.
• Implement RAG-based solutions for intelligent document retrieval and information extraction.
• Work with LangChain for LLM orchestration and application development.
• Develop document processing pipelines, including text extraction, parsing, chunking, and data extraction.
• Integrate LLM APIs into existing applications and workflows.
• Optimise application performance, scalability, and reliability.
• Collaborate with cross-functional teams to deliver AI-driven solutions.

Required Skills

• Strong programming experience in Core Python.
• Hands-on experience with FastAPI.
• Good knowledge of NumPy and Pandas.
• Experience in REST API development and integration.
• Practical experience with LangChain.
• Strong understanding of Retrieval-Augmented Generation (RAG).
• Knowledge of AI, Generative AI, and Large Language Models (LLMs).
• Experience in document processing and data extraction.

Job Overview

We are looking for an experienced AI/ML Engineer with strong full-stack development skills to design, develop, and deploy AI-powered applications. The ideal candidate should be proficient in Python backend development, frontend technologies, and LLM integration, with the ability to build end-to-end AI-native products, custom dashboards, and lightweight applications.

This role focuses on applying AI to real-world business problems through rapid prototyping, prompt engineering, Retrieval-Augmented Generation (RAG), and scalable application development.

Key Responsibilities

• Design, develop, and deploy end-to-end AI-powered applications.
• Build backend services and REST APIs using Python.
• Develop responsive frontends using React, Next.js, or similar frameworks.
• Integrate LLM APIs such as OpenAI, Claude, and Hugging Face into production applications.
• Build custom dashboards, internal tools, micro-apps, and AI-driven business solutions.
• Implement prompt engineering, embeddings, RAG pipelines, and context-aware AI systems.
• Rapidly prototype and validate ideas using modern AI-assisted development workflows.
• Optimize application performance, scalability, reliability, and AI usage costs.
• Work with data processing libraries such as Pandas and NumPy.
• Collaborate with product and business teams to translate requirements into functional AI solutions.
• Take ownership of features from ideation and development through testing, deployment, and production support.

Required Skills & Qualifications

• 2+ years of experience in software engineering, AI engineering, or application development.
• Strong proficiency in Python and backend development.
• Hands-on experience with React, Next.js, or similar frontend technologies.
• Practical experience integrating LLM APIs such as OpenAI, Claude, or Hugging Face.
• Understanding of REST APIs, microservices, and system design principles.
• Knowledge of prompt engineering, embeddings, and RAG architectures.
• Experience with data processing using Pandas and NumPy.
• Ability to independently build, test, and deploy full-stack applications.
• Strong problem-solving, debugging, and analytical skills.
• Ability to work in a fast-paced environment with a strong ownership mindset.

Good to Have

• Experience with LangChain, LlamaIndex, or similar AI frameworks.
• Familiarity with vector databases such as Pinecone, Weaviate, or Supabase.
• Experience building AI chat interfaces, copilots, assistants, and custom dashboards.
• Familiarity with cloud platforms, application deployment, and production monitoring.
• Experience with AI-assisted coding tools and rapid prototyping workflows.

What We Are Looking For

• A full-stack AI engineer who is comfortable working across both backend and frontend development.
• Someone focused on building practical AI-powered products rather than only training machine learning models.
• A developer who can prototype quickly, validate ideas, and iterate efficiently using a “vibe coding” approach.
• A self-driven professional who can take ownership of a feature from concept to production.

Please note that this job is only for Ahmedabad location.

Job Summary

We are looking for an experienced Python Developer with strong expertise in Generative AI (GenAI), Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG). The ideal candidate should have hands-on experience building and deploying AI-powered applications using Python, LangChain/LangGraph, and FastAPI.

Key Responsibilities

• Design, develop, and maintain scalable backend applications using Python.
• Build and implement Generative AI solutions using LLMs.
• Develop and optimize RAG-based applications and pipelines.
• Work with LangChain and LangGraph to build LLM-powered workflows and AI agents.
• Develop RESTful APIs and backend services using FastAPI.
• Integrate LLMs with enterprise applications, databases, and external services.
• Implement prompt engineering, context management, and response optimization.
• Work on vector databases and embedding models for semantic search.
• Ensure application scalability, performance, security, and reliability.
• Collaborate with cross-functional teams to deliver AI-driven solutions.

Mandatory Skills

• Strong hands-on experience in Python development.
• Practical experience with Generative AI and LLMs.
• Strong understanding and implementation experience of RAG architecture.
• Hands-on experience with LangChain and/or LangGraph.
• Experience developing REST APIs using FastAPI.
• Good understanding of LLM integration and prompt engineering.

Good to Have Skills

• Experience with OpenAI, Azure OpenAI, or other LLM providers.
• Knowledge of vector databases such as Pinecone, FAISS, Chroma, or Weaviate.
• Experience with embeddings and semantic search.
• Knowledge of Docker, Kubernetes, and cloud platforms (AWS/Azure).
• Exposure to AI agents and multi-agent systems.
• Experience with CI/CD and production deployment of AI applications.

About LeadSquared

LeadSquared is a leading sales execution and marketing automation platform trusted by 2,000+ businesses globally, including healthcare, education, financial services, and real estate. Headquartered in Bengaluru with offices across the US, UK, UAE, and Southeast Asia, we empower sales teams to close faster, smarter, and at scale.

Our AI team is at the forefront of integrating cutting-edge large language model capabilities into enterprise workflows — building intelligent agents, copilots, and automation systems that redefine how businesses operate.

Role Overview

We are looking for a Senior AI Engineer with hands-on experience building LLM-powered agents and agentic AI systems. You will design, develop, and deploy autonomous AI pipelines that solve complex, multi-step business problems — from lead qualification and follow-up automation to intelligent CRM workflows and beyond.

This role is ideal for someone who is deeply excited about the frontier of AI, can move fast, and wants their work to directly impact millions of sales professionals worldwide.

Key Responsibilities

•

Design and build LLM-powered agentic systems using frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI to automate complex, multi-step workflows.

•

Develop and maintain Retrieval-Augmented Generation (RAG) pipelines with vector databases (Pinecone, Weaviate, Chroma, pgvector) for domain-specific knowledge grounding.

•

Build and integrate tool-use and function-calling capabilities into AI agents, enabling dynamic interaction with internal APIs, databases, and third-party services.

•

Implement prompt engineering strategies including chain-of-thought, few-shot prompting, and structured output parsing to ensure reliable agent behavior.

•

Design evaluation frameworks and observability pipelines (LangSmith, Helicone, custom metrics) to monitor agent performance, accuracy, and cost.

•

Collaborate with product, sales, and domain teams to translate business requirements into AI-driven solutions and features.

•

Optimize LLM inference for latency and cost using techniques like caching, model distillation, quantization, and batching.

•

Stay current with the rapidly evolving LLM ecosystem and proactively propose improvements and new approaches.

•

Contribute to internal best practices, documentation, and knowledge-sharing across the engineering org.

Required Qualifications

Experience

•

2–4 years of professional software engineering experience, with at least 1–2 years focused on LLM/AI systems.

•

Proven experience shipping LLM-based products or agentic AI systems into production environments.

Technical Skills

•

Strong proficiency in Python and familiarity with async programming patterns for AI pipelines.

•

Hands-on experience with LLM APIs: OpenAI (GPT-4o), Anthropic (Claude), Google (Gemini), or open-source models (Llama, Mistral).

•

Experience with agentic frameworks: LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or similar.

•

Solid understanding of RAG architectures, embedding models, and semantic search.

•

Experience with vector databases and similarity search infrastructure.

•

Knowledge of REST APIs, microservices architecture, and containerization (Docker/Kubernetes).

Problem-Solving & Mindset

•

Strong ability to decompose ambiguous, open-ended problems into structured AI system designs.

•

Experience with prompt debugging, LLM evaluation, and iterative refinement workflows.

•

Ability to balance research exploration with engineering pragmatism to ship reliable systems.

Preferred Qualifications

•

Experience with multi-agent orchestration and agent memory systems (short-term and long-term).

•

Familiarity with fine-tuning or RLHF workflows for domain adaptation.

•

Background in NLP, information retrieval, or conversational AI.

•

Prior experience in B2B SaaS or CRM domain is a plus.

•

Contributions to open-source AI/ML projects or published research/blogs.

•

Experience with cloud platforms: AWS, GCP, or Azure — particularly AI/ML services

Product Engineer — Role Summary

We are looking for a Product Engineer to build user-facing products that combine AI capabilities with practical applications. You will work at the intersection of software engineering and AI, developing autonomous, agent-driven systems that solve complex educational and research problems.

Key Responsibilities:

• Product Development: Design, build, and deploy production-ready applications powered by LLMs and AI agents.
• Data Engineering: Build scalable ETL/ELT pipelines to process structured and unstructured data, including text and audio, for RAG and model fine-tuning.
• Agentic Workflows: Develop multi-step AI agents with tool calling, APIs, databases, search, reasoning, and memory.
• Rapid Prototyping: Turn ideas and research concepts into interactive, production-ready applications.
• AI Integration: Use frameworks such as LangChain, LlamaIndex, AutoGen, or custom orchestrators to integrate AI into scalable systems.
• User Experience: Transform raw AI outputs into reliable, intuitive, and responsive user experiences.
• Collaboration: Work closely with ML researchers and data engineers to integrate custom and fine-tuned models.
• Observability: Monitor agent behavior, manage edge cases, reduce hallucinations, and improve reliability in production.

The ideal candidate combines strong software engineering, AI/LLM expertise, data engineering, and product thinking, with the ability to take an AI concept from prototype to production.

Job Summary

We are looking for a skilled Python Developer with experience in Generative AI and Agentic AI to develop AI-powered applications and scalable backend services.

Mandatory Skills

• Python
• Generative AI (GenAI) / Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• LangChain / LangGraph
• Agentic AI
• FastAPI
• REST API development
• Vector Databases
• Prompt Engineering
• Microservices

Key Responsibilities

• Develop and maintain Python-based applications and backend services.
• Build GenAI/LLM-powered applications and AI solutions.
• Implement RAG pipelines for document processing and information retrieval.
• Develop AI agents using LangChain/LangGraph and Agentic AI frameworks.
• Build and integrate REST APIs using FastAPI.
• Work with vector databases for embeddings, semantic search, and retrieval.
• Design and optimize prompts to improve LLM response quality.
• Develop scalable microservices and integrate AI models into applications.
• Collaborate with cross-functional teams to deliver AI-based solutions.
• Troubleshoot, test, and optimize application performance.

Required Qualifications

• 4–6 years of experience in Python development.
• Hands-on experience with GenAI/LLMs, RAG, and Agentic AI.
• Practical experience with LangChain/LangGraph, FastAPI, and REST APIs.
• Knowledge of vector databases, prompt engineering, and microservices.
• Strong problem-solving and debugging skills.
• Ability to develop and deploy production-ready AI applications.

🚀 Hiring: Python GenAI / Agentic AI Engineer

📍 Location: Hyderabad

💼 Experience: 7+ Years

🤖 GenAI / Agentic AI: 2+ Years

Mandatory Skills:

• Strong Python development experience

• Generative AI / Agentic AI

• LLMs & Prompt Engineering

• LangChain / LangGraph

• RAG & Vector Databases

• AI Agents / Multi-Agent Systems

• FastAPI / REST APIs

• LLM Integration

• Microservices & API Architecture

• Git & CI/CD

Looking for candidates with strong hands-on experience in building GenAI/Agentic AI solutions using Python, LLMs, RAG, and AI Agent frameworks.

Role: Python + Agentic AI Engineer

We are looking for an experienced Python + Agentic AI Engineer with strong expertise in developing AI-powered applications and autonomous agent-based solutions.

Key Skills / Requirements:

• Strong hands-on experience in Python

• Experience with Agentic AI / AI Agents

• Hands-on with LangChain / LangGraph or similar agent frameworks

• Experience with Generative AI and LLMs

• Strong understanding of RAG (Retrieval-Augmented Generation) and Vector Databases

• Experience developing REST APIs using FastAPI

• Knowledge of Multi-Agent Systems, Tool/Function Calling and Agent Workflows

• Experience integrating LLMs with enterprise applications/APIs

• Exposure to cloud-based AI services is an advantage

Preferred Profile: Python Developer / AI Engineer / Generative AI Engineer / Agentic AI Engineer with hands-on experience building production-ready AI solutions.

Note: Only Immediate joiners are considered

Key Skills:

• Builds AI-powered business applications end to end, from the Python/FastAPI service layer through to React-based user interfaces, deployed on Databricks
• Designs and builds APIs connecting AI agents, governed data and user-facing workflows, including decision capture, audit logging and file exports for downstream systems
• Codes rule-based decision engines in Python (e.g. allocation or replenishment logic) that work alongside ML models
• Integrates LLM agent runtimes into applications, including tool calls, streamed responses and cited outputs
• Writes performant SQL against governed data and ensures services operate within defined access boundaries
• Builds interactive screens, dashboards and conversational interfaces that let users review and act on AI recommendations
• Works closely with GenAI/ML engineers, data engineers and BA

Primary tech stack:

Python, Fast API, REST API design, SQL, Databricks Apps, Databricks SQL, Unity Catalog, LLM agent integration, React, TypeScript, Git / CI-CD

Secondary tech stack:

Pydantic, Async Python, Pytest, MLflow, Delta Lake, State management, Figma-to-code

Job Description-

Location- Bengaluru

Experience-5-7 years

Wissen is building the engineering team for RES Modernization, a corporate services programme at a leading global financial services firm, rebuilding the lease and real estate management platform on a cloud stack with AI and agentic capability designed in rather than bolted on. The AI Solution Engineer builds that product: .NET services and APIs at the core, Python wherever the AI, retrieval and data work lives. We want a strong .NET engineer who has moved into Python, not a Python specialist who once touched C#.

• Build features end to end on a .NET codebase: C# and ASP.NET Core services, the APIs above them, and the React or Angular front end where a feature needs one.
• Write the Python that carries the AI work — retrieval and grounding, prompt and agent orchestration, evaluation harnesses, and the pipelines that feed them.
• Put LLM and agentic capability into real product workflows, with the grounding, guardrails and cost and latency budgets a regulated environment demands.
• Take your work through the client's engineering and change review: design notes, test evidence, security and code-quality gates.
• Work with the stream's data and integration engineers on the Snowflake and integration layer the product reads from.