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SB-1486-AI Engineer Intern
Job Location:
Monthly Salary:
Posted:
21 August 2026 (2 days ago)
Posted:
Application Deadline:
18 November 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Department:
Job Summary
AI Engineer Intern
Role Summary
We are looking for five AI Engineering Interns to learn and contribute to production-grade agentic AI systems alongside our engineers. This is a hands-on mentored internship centred on multi-agent orchestration context management and large language model (LLM) integration. It is open to final-year students and recent graduates what matters most is outstanding computer-science fundamentals strong data structures and algorithms (DSA) skills and hands-on ability with Python.
You will work under the guidance of senior engineers on agent workflows and the context architecture behind them contributing to real features while building production-grade skills. The ideal intern has a strong academic record sharp problem-solving ability genuine enthusiasm for the agentic AI stack and the drive to convert this internship into a full-time AI Engineer role.
Key Responsibilities
Agent Orchestration & Workflow
- Assist in designing and implementing multi-agent workflows using LangGraph on Python with Pydantic structured output under the guidance of senior engineers.
- Help model processes as stateful resumable graphs with branching looping retries and checkpointing.
- Support implementation of safe pause/resume and human-in-the-loop (HITL) checkpoints.
Context Engineering
- Learn and contribute to context management layered context retrieval/indexing and active working sets.
- Help implement context selectors and filters token-budgeted prompts and summarisation/compaction of long histories.
- Assist in designing typed context schemas so each agent step receives precise high-signal context.
LLM Integration & Retrieval
- Integrate LLM providers (e.g. Anthropic OpenAI / Azure OpenAI) using prompt engineering tool calling and structured output with mentorship.
- Help wire in retrieval vector search and embeddings and code-intelligence techniques for working over large codebases.
- Contribute to model-routing experiments that balance task type latency and cost.
Quality Evaluation & Governance
- Help build evaluation and error-analysis loops; learn to treat failures as feedback that improves reliability.
- Assist in implementing verification and validation patterns and deterministic gates for agent outputs.
- Help keep agent decisions and context observable auditable and reproducible.
Collaboration
- Work with platform/infrastructure engineers on deployment inference and persistence tasks.
- Participate in design reviews code reviews and Demo Friday sharing your work including failed experiments.
Required Technical Skills
| Domain | Skills & Technologies | Must / Preferred |
| CS Fundamentals & DSA | Data structures algorithms complexity analysis strong problem-solving | Must |
| Programming | Python 3.10 (async typing); clean idiomatic code | Must |
| Agent Orchestration | LangGraph graphs/state machines checkpointers HITL interrupts | Good to have |
| Context Engineering | Layered context selectors/filters summarisation & compaction token budgeting | Good to have |
| Agentic AI Development | Multi-agent design tool calling structured output verification patterns | Good to have |
| LLM Integration | Anthropic & OpenAI / Azure OpenAI SDKs prompt engineering | Preferred |
| Data Modelling | Pydantic v2 JSON Schema / typed contracts | Preferred |
| Retrieval | Vector stores (e.g. Qdrant / Azure AI Search) embeddings | Preferred |
| Context Protocol | Model Context Protocol (MCP) resources/tools Streamable HTTP | Preferred |
| Multi-agent Frameworks | CrewAI Microsoft Agent Framework | Preferred |
| Durable Workflows | Temporal (long-running resumable flows) | Preferred |
| Inference | vLLM awareness (paged attention batching quantisation) model routing | Preferred |
Qualifications & Certifications
- Pursuing or recently completed / B.E. / / MCA in Computer Science or a related field from a reputable institution (or equivalent).
- Final-year students and recent graduates welcome; strong fundamentals matter more than years of experience.
- Strong data structures algorithms and problem-solving skills a competitive-programming track record (Codeforces / LeetCode / ICPC / similar) is a strong plus.
- Hands-on Python plus any exposure to LLM / agentic AI through academic projects or self-learning with clear eagerness to go deep on LangGraph and context engineering.
Preferred Certifications
- Any recognised AI/ML or agentic-AI online course or certification (e.g. Anthropic Microsoft Azure AI Fundamentals).
- Any cloud fundamentals certification (Azure / AWS / GCP) is a plus.
Soft Skills & Cultural Fit
- Strong analytical mindset with a structured approach to design debugging and root-cause analysis.
- Clear written and verbal communication able to explain your approach to technical and non-technical people.
- Eagerness to learn high coachability and the ability to take and act on feedback.
- Collaborative team player who contributes to shared standards code reviews and knowledge sharing.
Required Experience:
Intern
About Company
Softobiz prepares businesses for transformative success by embracing change and engineering innovative digital products.
