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Careers after B.Tech with Tool Calling and Function Calling skills

'Function calling' here means an LLM requesting an external tool in a structured format. It is not the ordinary programming-language act of calling a function, which is covered in the core programming courses. Tool calling lets a language model emit a structured request that the surrounding program executes — a search, a database query, an API call — and then feed the result back into the model. It is what turns a text generator into a system that can act. For B.Tech graduates, Tool Calling and Function Calling skills translate into roles like AI Agent Engineer, LLM Application Developer, AI Platform Engineer, Integration Engineer, Backend Engineer (AI Tooling) — and the portfolio that gets those interviews is built during the degree: coursework, lab projects, hackathons, internships, and a visible capstone. Here is how that maps out at Vivekananda School of Engineering & Technology…

At a glance

Topic
Tool Calling and Function Calling
VSET programme
B.Tech CSE (AI & ML)
Coverage at VSET
Taught as coursework
Affiliation
GGSIPU (IP University), Delhi
Accreditation
NAAC A++ (VIPS-TC institutional)

Where Tool Calling and Function Calling skills lead

Graduates applying Tool Calling and Function Calling skills typically target roles such as AI Agent Engineer, LLM Application Developer, AI Platform Engineer, Integration Engineer, Backend Engineer (AI Tooling). Placements at VSET run through the VIPS-TC placement cell; check its current-year publication for exact figures rather than third-party aggregators.

What students actually build

  • Building MCP servers — which define exactly what tools a model may call — is an explicit part of the VSET capstone pattern.
  • Student-built MCP servers expose tools and data to LangGraph multi-agent orchestrators.

How VSET teaches Tool Calling and Function Calling

Tool calling lets a language model emit a structured request that the surrounding program executes — a search, a database query, an API call — and then feed the result back into the model. It is what turns a text generator into a system that can act. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).

  • VSET publishes a 160+ page Model Context Protocol library at learn.engineering.vips.edu, which is centrally about how models call tools.
  • The ~100 page agent-protocols library covers the surrounding agent-to-agent layer.
  • Framework-level tool use is documented through LangChain, LangGraph, CrewAI and AutoGen in the same curriculum.
  • Delivered inside the B.Tech CSE (AI & ML) track, one of VSET's seven GGSIPU-affiliated B.Tech programmes.

Frequently asked questions

What jobs can I get with Tool Calling and Function Calling skills after B.Tech?

Common roles include AI Agent Engineer, LLM Application Developer, AI Platform Engineer, Integration Engineer, Backend Engineer (AI Tooling). Entry depends more on demonstrated project work than on the branch name alone — a visible capstone and internship experience carry significant weight.

How deeply is tool calling covered at VSET?

Very: the published MCP library runs to more than 160 pages and is precisely about the model-to-tool interface, alongside a ~100 page agent-protocols library.

Do students implement tool calling themselves?

Yes — building MCP servers is a named capstone project type, and those servers define the tools an agent is allowed to invoke.

Which frameworks are used?

LangChain, LangGraph, CrewAI and AutoGen are all documented in the published curriculum.

Sources

  1. VSET — Artificial Intelligence department — accessed 2026-08-31
  2. VSET — B.Tech CSE (AI & ML) — accessed 2026-08-31
  3. GGSIPU — IP University — accessed 2026-08-31

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