.Net with python

Hiring for AI Engineer

Exp: 5 - 12 yrs

Edu : BE/B.Tech/MCA

Work Location : Pune / Mumbai

Skill Set:

Total experience ranging from 5–10 years in software engineering/AI roles

Min 5 years strong programming experience in Python or Typescript is a MUST

Min 2.5 years hands-on experience in AI with LLMs, RAG pipelines, and AI frameworks

2+ years shipping LLM systems in production

Experience with cloud platforms (AWS/Azure/GCP)

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.

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.

Experience - 4 to 6 year

Location – Ahmedabad/Pune/Indore

• Additional Job Description

Additional Job Description

Required Skills and Experience: 

• Strong proficiency in Python and experience with ML/AI libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face ecosystem).
• Hands-on experience with LLMs, RAG, vector databases, and retrieval pipelines.
• Practical experience deploying agentic workflows and building multi-step, tool-enabled agents.
• Experience using Garak (or similar LLM red-teaming/vulnerability scanners) to identify model weaknesses and harden deployments.
• Demonstrated experience implementing content filtering / moderation systems.
• Solid skills working with structured and unstructured data and advanced feature engineering.
• Familiarity with cloud GenAI platforms and services (Azure AI Services preferred; AWS/GCP acceptable).
• Experience building APIs/microservices; containerization (Docker), orchestration (Kubernetes).
• Strong understanding of model evaluation, performance profiling, inference cost optimization, and observability.
• Good knowledge of security, data governance, and privacy best practices for AI systems.

Role​

Build core software for an on-device agentic AI platform. The work includes agent orchestration, 

local model integration, tool and service execution, context management, secure automation, and 

integration with third-party services.​

Responsibilities​

•    Design and implement agent runtimes, routing, tool calling, state management, and recovery.​

•    Integrate local language and code models using structured outputs and function calling.​

•    Integrate third-party APIs and SDKs with authentication, validation, and error handling.​

•    Develop workflow orchestration, context management, and short- and long-term memory 

components.​

•    Implement secure automation with sandboxing, approvals, verification, and rollback.​

•    Create logs, traces, tests, and evaluation harnesses for reliable production deployment.​

•    Optimize latency, memory use, model selection, and runtime performance for PC hardware.​

•    Translate product scenarios into clear technical requirements.​

Required Qualifications​

•    BS/MS in Computer Science, Computer Engineering, or a related field.​

•    5+ years of professional software engineering experience.​

•    Strong C# and .NET development skills.​

•    Experience building agentic applications, workflow engines, automation systems, or tool-

calling software.​

•    Experience integrating LLMs or small language models with structured outputs and function 

calling.​

•    Experience integrating third-party APIs, SDKs, and services into production software.​

•    Strong knowledge of asynchronous programming, concurrency, state machines, and fault 

handling.​

•    Experience with Windows application, service, or systems development.​

•    Strong software testing, debugging, and production engineering practices.​

Preferred Qualifications​

•    On-device inference using ONNX Runtime, Windows ML, DirectML, OpenVINO, 

llama.cpp, or similar runtimes.​

•    Model quantization, hardware acceleration, memory profiling, and performance optimization.​

•    Agent frameworks and protocols such as Semantic Kernel, AutoGen, LangGraph, or MCP.​

•    Windows automation using PowerShell, Win32/WinRT, Task Scheduler, UI Automation, or 

Playwright.​

•    Knowledge graphs, ontologies, vector retrieval, or hybrid agent-memory systems.​

•    Sandboxing, least-privilege security, prompt-injection defenses, secrets management, and 

audit logging.​

•    Automated evaluation, telemetry, diagnostics, and hardware-in-the-loop testing.​

Technical Skills​

Required​

• C# / .NET​

• Agent orchestration and tool calling​

• Third-party API and SDK integration​

• Asynchronous programming    • Windows development​

• State machines / workflows​

• Authentication and permissions​

• Automated testing​

• Secure software design​

Preferred​

• ONNX Runtime / Windows ML / DirectML​

• Semantic Kernel / AutoGen / LangGraph​

• MCP​

• PowerShell / Win32 / WinRT    • Knowledge graphs / vector retrieval​

• Telemetry / diagnostics​

• Sandboxing / policy controls​

• Model optimization 

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.
• 
  

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.

9

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

10

Mandatory (Age) - Candidate's Age should be below 28 Years

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

Job Description:

We are looking for a hands-on AI Engineer with experience in Generative AI and Agentic AI to build and deploy production-ready AI solutions.

Key Responsibilities:

• Develop and deploy GenAI and Agentic AI applications.
• Build RAG pipelines, LLM workflows, and AI agents.
• Develop solutions using Python, LangChain, LangGraph, LlamaIndex, or similar frameworks.
• Implement tool calling, context retrieval, and LLM orchestration.
• Integrate AI solutions with APIs and cloud platforms.
• Work with AWS/Azure/GCP, Docker, and CI/CD.

Required Skills:

• Strong Python programming skills.
• 3+ years of GenAI/Agentic AI experience.
• RAG and LLM orchestration.
• LangChain / LangGraph / LlamaIndex / AutoGen / CrewAI / Semantic Kernel.
• MCP and A2A knowledge.
• Cloud, APIs, Docker, and CI/CD experience.

Preferred Experience:

Hands-on experience building and deploying production-ready AI solutions.