.Net with python

What you need • • • • • • Delivered inside a regulated environment: code review, change control, a real audit trail. Based in, or able to relocate to, Bengaluru or Mumbai for the engagement. 7–15 years building production software, with .NET (C#, ASP.NET Core) as your primary stack. Python you have shipped and maintained — services, pipelines or AI components other people depend on, not occasional scripting. Hands-on work with LLMs in production: retrieval-augmented generation, prompt and agent design, and a clear account of how you evaluated whether it worked. Comfortable across SQL, REST and asynchronous integration patterns, on Azure or AWS, with CI/CD, containers and infrastructure as code. Good to have • • Migration work from .NET Framework to modern .NET. Azure OpenAI, Semantic Kernel, LangChain or LlamaIndex. • • Snowflake, including Cortex. Real estate, lease management or corporate services domain exposure

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.

Strong AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.

3

Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.

4

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

5

Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.

6

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

7

Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.

8

Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

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

Software Engineer II to join Planview’s Keyedin team.

Planview is an enterprise software company focused on portfolio and work management, helping organizations plan, prioritize, and deliver work across strategy, teams, and technology. Its product portfolio spans project and portfolio management (PPM), enterprise agile planning, product portfolio management, and work management tools — including offerings like AdaptiveWork, Planview PPM Pro, ProjectPlace, Planview Viz, and Deliver (One2Team), plus its ProjectAdvantage (formerly Sciforma) product for project and resource management. The company serves a wide range of industries, from financial services to technology to government, helping large organizations connect strategy to execution and manage complex portfolios of projects, products, and resources.

About the Role:

You’ll work on a product that combines legacy and modern technologies, contributing across the full stack while helping shape future platform integrations, connectors, and AI-powered capabilities. You’ll also work directly on customer-facing tickets and real-world product challenges, gaining hands-on exposure to the application and its technology stack from day one.

What You’ll Work On

• Customer-facing development and product enhancements
• Platform integrations and connector development
• Cloud technologies and AI-enabled capabilities
• Maintenance and modernization of existing product functionality
• Collaboration on new technologies as the platform evolves

Must-Have Skills

• C#/.NET, MVC, VB.NET, Web API, and Dapper
• Angular, HTML, CSS, and JavaScript/TypeScript
• Unit testing using NUnit, Jasmine, and Karma
• IIS
• SQL Server, including functions, stored procedures, and scheduled jobs
• Experience with AI coding tools such as Claude, GitHub Copilot, or similar

Nice-to-Have Skills

• Integration testing
• Azure DevOps
• Power BI
• Cloud platforms such as Azure or AWS

Growth Opportunity

Over the next 1–2 years, you’ll have the opportunity to progress from handling customer-facing issues to owning complex technical problems and key product areas. You’ll build expertise across legacy and modern technologies, integrations, cloud, and AI, with a path toward leading technical initiatives, contributing to architectural and product decisions, mentoring engineers, and progressing toward a senior or technical leadership role.

Team Culture and Work Style

The Keyedin team is learning-focused, collaborative, and customer-focused. This role follows a hybrid work model with two days per week in the office and no shift work.

If this opportunity aligns with your experience and career goals, please share your updated resume and let me know a convenient time to connect.

Strong Senior AI Engineer Profile with production-grade LLM and Python expertise

2

Mandatory (Experience 1): Must have at least 3+ years of professional AI/ML engineering experience with demonstrated track record of delivering production-grade AI systems in real-world environments

3

Mandatory (Tech skill 1): Must have strong programming skills in Python and SQL, with hands-on ML/data libraries (scikit-learn, pandas, numpy) and deep-learning frameworks (PyTorch or TensorFlow), plus REST API design

4

Mandatory (Experience 2): Must have hands-on experience building and deploying production-grade ML/LLMs including RAG pipelines, document parsing, information extraction, and text processing on large-scale unstructured data (preprocessing, chunking, embeddings, feature engineering)

5

Mandatory (Tech skill 2): Must have strong NLP / extraction-focused ML depth — transformers, embeddings, vector databases, RAG, LLM integrations, and agentic workflows.

6

Mandatory (Tech skill 3): Must have hands-on experience with AWS (SageMaker, Bedrock, EC2, Lambda) and Azure (AI Foundry, Azure OpenAI) for model training, fine-tuning, deployment, and inference at scale

7

Mandatory (Tech skill 4): Must have experience with multi-agentic frameworks / orchestration tools (Claude Code, LangGraph, LangChain, CrewAI)

8

Mandatory (Tech skill 5): Must have hands-on experience with MLOps ecosystem including experiment tracking (MLflow, Weights & Biases), model versioning/registry, automated retraining, and CI/CD (GitHub Actions, Azure DevOps, Docker, Kubernetes)

9

Mandatory (Tech skill 6): Must have experience with evaluation frameworks (precision, recall, F1, field-level accuracy) and iterative model improvement, plus AI observability (Prometheus, Grafana, SLOs).

10

Mandatory (Team Leadership): Must have experience leading projects or teams, managing technical deliverables, and mentoring, with strong problem-solving in ambiguous challenges

11

Mandatory (Education) - B.Tech or B.E. If graduated in BCA or BCS, they should have a Maters or Post graduation

12

Mandatory (Company): B2B Tech/Consulting/B2B Software

Job Description – Python & Generative AI Engineer

Python & Generative AI Engineer

Location: Bangalore, India

Experience: 4+ Years

Employment Type: Full-time

Job Summary

We are looking for an experienced Python & Generative AI Engineer with 4+ years of software development experience and strong hands-on expertise in Python, LLMs, Generative AI, and AI application development.

The ideal candidate should be comfortable building production-grade AI solutions, integrating LLMs with enterprise applications, and developing scalable APIs and services using Python.

Key Responsibilities

• Design, develop, and deploy Generative AI applications using Python and modern AI/ML frameworks.
• Work with Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, or similar models.
• Develop RAG (Retrieval-Augmented Generation) pipelines using vector databases and embedding models.
• Build AI-powered applications using frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent.
• Develop scalable REST APIs and backend services using FastAPI, Flask, or Django.
• Integrate LLM APIs, prompt engineering, function/tool calling, and structured outputs into enterprise applications.
• Work with vector databases such as FAISS, Pinecone, Weaviate, Milvus, or Azure AI Search.
• Implement document processing, chunking, embeddings, semantic search, and knowledge retrieval solutions.
• Evaluate LLM responses for accuracy, relevance, hallucination, latency, and cost.
• Build and maintain production-ready AI pipelines with appropriate monitoring, logging, security, and error handling.
• Collaborate with data scientists, ML engineers, software engineers, and business stakeholders to deliver AI solutions.
• Write clean, reusable, testable, and well-documented Python code.
• Participate in architecture discussions, code reviews, testing, deployment, and production support.

Required Skills

• 4+ years of experience in software/Python development.
• Strong proficiency in Python and object-oriented programming.
• Hands-on experience with Generative AI and LLM-based applications.
• Experience with OpenAI/Azure OpenAI, Anthropic, Google Gemini, or open-source LLMs.
• Strong understanding of Prompt Engineering and LLM application patterns.
• Experience implementing RAG pipelines.
• Knowledge of embeddings, vector databases, semantic search, and document retrieval.
• Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.
• Strong experience developing REST APIs using FastAPI/Flask/Django.
• Familiarity with Git, CI/CD, Docker, and cloud platforms such as AWS, Azure, or GCP.
• Good understanding of SQL and databases.
• Strong problem-solving and communication skills.

Good to Have

• Experience with AI agents / Agentic AI and tool/function calling.
• Experience with multi-agent frameworks.
• Knowledge of MLOps/LLMOps and model evaluation.
• Experience with Kubernetes and containerized deployments.
• Knowledge of NLP, machine learning, or deep learning.
• Experience with Azure AI, AWS Bedrock, Amazon SageMaker, or Google Vertex AI.
• Understanding of responsible AI, data privacy, and LLM security.

Education

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.

Required Skills:

• Strong C#/.NET development and experience building Agentic AI applications, workflow engines, automation systems, or tool-calling software.
• LLM/SLM integration with structured outputs and function calling.
• Third-party API/SDK integration.
• Asynchronous programming, concurrency, state machines, and fault handling.
• Windows application, service, or systems development.
• Authentication, permissions, secure software design, automated testing, and debugging.
• Bachelor's/Master's degree in Computer Science, Computer Engineering, or related field.

Preferred Skills:

• ONNX Runtime, Windows ML, DirectML, OpenVINO, or llama.cpp.
• Semantic Kernel, AutoGen, LangGraph, or MCP.
• PowerShell, Win32/WinRT, UI Automation, or Playwright.
• Knowledge graphs, vector retrieval, and agent memory.
• Model optimization, telemetry, diagnostics, sandboxing, and security.
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About the role

We are seeking an AI Engineer to build and implement AI systems for content production at scale. You'll work at the intersection of engineering and content designing prompt pipelines, integrating generative models, and building the tooling that turns source material into finished creative output. The ideal candidate is technically strong but also has taste: someone who understands story and craft, and can tell the difference between output that's technically correct and output that's actually good.

Responsibilities

• Build and iterate on prompt pipelines and multi-agent workflow components
• Design and integrate agentic workflows orchestrate multi-step, tool-using agents that plan, call models, and hand off between stages in production
• Deploy and serve open-source models set up inference endpoints, manage GPU compute, and optimize for latency and cost
• Write evals compare outputs against references, quantify quality, and feed results back into the pipeline
• Work on data pipelines: structured extraction from messy source text, localization, similarity/dedup
• Debug and maintain pipeline stages in production

What you bring:  

• (1+/3+) years of engineering experience, or a strong portfolio of shipped projects
• Solid Python fundamentals clean, working, readable code
• Hands-on experience with LLM APIs and prompt engineering (personal projects count)
• Comfort with Git, REST APIs, and working in a Linux environment
• A feel for content and narrative you can judge whether generated output is actually good, not just valid
• Curiosity and clear communication you ask good questions and don't stay stuck silently

 Preferred

• Exposure to agent/orchestration frameworks (LangGraph, LangChain, CrewAI)
• Familiarity with vector databases, embeddings, or RAG (Qdrant, pgvector)
• Hands-on work with open-source generative media models Flux, LTX, Wan, or similar
• Experience deploying open-source models for inference (vLLM, ComfyUI, Replicate/Cog, Docker + GPU)
• Experience writing evals or LLM-as-judge scoring
• Node.js and Fastapi familiarity, or experience deploying on AWS

About the role

We are seeking an AI Engineer to build and implement AI systems for content production at scale. You'll work at the intersection of engineering and content designing prompt pipelines, integrating generative models, and building the tooling that turns source material into finished creative output. The ideal candidate is technically strong but also has taste: someone who understands story and craft, and can tell the difference between output that's technically correct and output that's actually good.

Responsibilities

• Build and iterate on prompt pipelines and multi-agent workflow components
• Design and integrate agentic workflows orchestrate multi-step, tool-using agents that plan, call models, and hand off between stages in production
• Deploy and serve open-source models set up inference endpoints, manage GPU compute, and optimize for latency and cost
• Write evals compare outputs against references, quantify quality, and feed results back into the pipeline
• Work on data pipelines: structured extraction from messy source text, localization, similarity/dedup
• Debug and maintain pipeline stages in production

What you bring:  

• (1+/3+) years of engineering experience, or a strong portfolio of shipped projects
• Solid Python fundamentals clean, working, readable code
• Hands-on experience with LLM APIs and prompt engineering (personal projects count)
• Comfort with Git, REST APIs, and working in a Linux environment
• A feel for content and narrative you can judge whether generated output is actually good, not just valid
• Curiosity and clear communication you ask good questions and don't stay stuck silently

 Preferred

• Exposure to agent/orchestration frameworks (LangGraph, LangChain, CrewAI)
• Familiarity with vector databases, embeddings, or RAG (Qdrant, pgvector)
• Hands-on work with open-source generative media models Flux, LTX, Wan, or similar
• Experience deploying open-source models for inference (vLLM, ComfyUI, Replicate/Cog, Docker + GPU)
• Experience writing evals or LLM-as-judge scoring
• Node.js and Fastapi familiarity, or experience deploying on AWS

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.