AI Application Engineer

AI Application Engineer

Agentic Systems and Intelligent Automation

Multiple Openings | Full-time

About Ajentica

Ajentica is an AI-native product engineering company helping ambitious software businesses become truly agentic.

We partner with growth-stage and private-equity-backed companies to modernize complex platforms, redesign operational workflows and build intelligent systems that work alongside peoplenot merely generate content. Our work spans agentic automation, enterprise software modernization, intelligent product development and AI-enabled delivery across healthcare, pharmacy, compliance, HR technology and other operationally complex industries.

From HIPAA-sensitive clinical workflows and autonomous desktop agents to platform integration and AI-assisted software development, we focus on moving AI beyond prototypes and into secure, measurable and production-ready systems.

About the Role

We are looking for well-rounded, highly capable software engineers (2 - 8 years of experience, IIT/NIT/Tier 1 background preferred) who can apply AI to real business and engineering problems.

This is not a prompt-engineering role, nor is it focused on developing foundational AI models. You will be a software engineer first—designing applications, services and workflows that use LLMs, multimodal models, and other AI capabilities where they create meaningful value.

You may work on agentic workflows, intelligent automation, enterprise platform integration, software modernization, document processing, browser or desktop automation, knowledge retrieval and human-in-the-loop systems.

The role requires both applied AI capability and meaningful depth in at least one broader area of software engineering (full-stack or backend development, distributed systems, data engineering, or devops).

What You’ll Do

• Design, build and maintain production-grade AI-enabled applications and services.
• Translate business processes and operational problems into practical technical solutions.
• Integrate LLMs and other AI services with APIs, databases, enterprise platforms and existing software products.
• Build agentic workflows that can reason within defined boundaries, use tools and complete multi-step tasks.
• Develop backend services, APIs, event-driven processes and data pipelines supporting AI applications.
• Build retrieval and grounding solutions using structured and unstructured business data.
• Implement human review, approval and escalation mechanisms for sensitive or uncertain decisions.
• Design evaluations to measure accuracy, reliability, latency, cost and business outcomes.
• Implement logging, tracing, monitoring and observability for AI-enabled workflows.
• Handle model failures, unavailable services, incomplete data and other real-world exceptions safely.
• Write automated tests and participate in code reviews, architecture discussions and technical discovery.
• Take solutions from early investigation and prototyping through deployment, iteration and production support.
• Work closely with product managers, architects, domain experts and client engineering teams.
• Contribute to reusable engineering patterns, internal accelerators and Ajentica’s broader AI delivery capabilities.

Core Qualifications

• A degree from an IIT, NIT, or other Tier 1 institution and significant work experience in well-respected companies are strongly preferred.
• Strong software engineering fundamentals and experience building production applications with significant usage.
• You are a fast, sharp thinker who accurately analyses problems, is skilled at clarifying ambiguous requirements, and possesses very strong English communication skills. You possess a high level of attention to detail and the proactiveness to flag issues and propose improvements.
• Proficiency in at least one production programming language, such as Python, TypeScript, C#, Java, or Go. Ability to work effectively with Python where required for AI application development.
• Familiarity with disciplined AI-based software development and the practices emerging around it.
• Experience designing and integrating APIs, services and databases.
• Understanding of system design, data modelling, testing and maintainable software architecture.
• Familiarity with Git, CI/CD, containerization and cloud deployment.
• Experience with monitoring, debugging and supporting applications in production.
• Ability to investigate ambiguous problems, test assumptions and make sound engineering trade-offs.

Broader Engineering Depth

Candidates should demonstrate meaningful experience in at least one of the following areas:

• Full-stack or backend engineering: Web applications, APIs, service architecture, authentication and modern application frameworks.
• Distributed systems: Event-driven systems, messaging, asynchronous processing, workflow orchestration and resilient services.
• Data engineering: Data pipelines, transformation, storage, search, data quality and analytical platforms.
• Cloud and DevOps engineering: Infrastructure, containers, CI/CD, deployment automation, observability, security and operational reliability.

Candidates with exceptional depth in applied AI engineering will also be considered.

Applied AI Experience

• Practical experience building applications using LLMs or other commercially available AI models and running them in production at scale. We prefer candidates who have run and maintained AI systems professionally.
• Experience with model APIs, structured outputs, function calling or tool use.
• Understanding of common agentic patterns, including workflow orchestration, routing, state management and human oversight.
• Familiarity with retrieval-augmented generation, embeddings, semantic search or knowledge-grounded systems.
• Ability to assess when AI is appropriate and when conventional software or rules would be safer and more effective.
• Awareness of common AI application risks, including hallucination, prompt injection, unsafe tool use and unintended data exposure.
• Understanding of how to evaluate and improve AI application quality rather than relying solely on subjective demonstrations.

Experience with frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen or similar platforms is helpful, but we value sound engineering judgement over familiarity with any particular framework.

Nice to Have

• Experience integrating third-party OCR, document-processing, computer-vision or multimodal AI libraries/services.
• Browser automation, Windows desktop automation or UI automation experience.
• Experience with workflow engines, queues or distributed task-processing systems.
• Voice automation, speech-to-text, text-to-speech or IVR integration experience.
• Familiarity with MCP, tool registries or similar integration protocols.
• Experience developing software for healthcare, pharmacy, financial services or other regulated environments.
• Familiarity with HIPAA, PHI handling, financial compliance, data privacy, auditability or security-sensitive systems.
• Experience working directly with international clients or distributed engineering teams.

What Good Looks Like

You understand that an impressive prototype is only the beginning. A successful AI application must also be reliable, observable, secure, maintainable and commercially sensible.

You do not reach for an LLM simply because one is available. You can distinguish between problems requiring AI, deterministic software, traditional automation or a combination of approaches.

You are comfortable moving quickly during discovery while maintaining engineering discipline. You can explain your decisions, test your assumptions and take ownership of what you put into production.

How We Work

Ajentica follows an AI-first engineering approach. Our engineers use modern development tools such as Claude Code, Codex, Pi, Cursor, GitHub Copilot and equivalent platforms to accelerate investigation, development and testing.

AI-assisted work must still be understood, validated and owned by the engineer. We value speed, but we place equal importance on accountability, technical judgement and software quality.

What You’ll Get

• The opportunity to build AI applications for real operational environments.
• Exposure to international clients and complex enterprise problems.
• Ownership across discovery, architecture, implementation and production deployment.
• Opportunities to work across agentic systems, intelligent automation and modern software engineering.
• A growing engineering environment where strong contributors can influence technical standards, delivery practices and future products.

How to Apply

Please submit your CV and LinkedIn profile, along with links to your GitHub, portfolio or relevant projects where available.

We would particularly like to hear about:

• A production software system you helped design or build.
• An AI-enabled application or automation you have implemented.
• The broader engineering area in which you have the strongest depth.
• Your individual contribution and the technical decisions you personally owned.

Ajentica values demonstrated engineering ability over buzzwords. If you have built meaningful systems but do not meet every listed requirement, we would still like to hear from you.