How Agentic AI is Redesigning Job Roles for Engineers

Across India’s enterprises, from IT services and consulting to manufacturing and education, AI has shifted the centre of gravity of work. According to an EY survey of over 200 Indian enterprise leaders assessing their experience with generative AI and agentic AI, organisations have clearly advanced in their AI journey, with nearly half now reporting multiple live use cases.

AI adoption has clearly moved pilots. However, large-scale integration is still in early stages, with only 10% organisations reporting enterprise-wide deployment. This has also created new job roles like agentic engineers who can develop and deploy AI agents.

“Agentic AI is fundamentally changing the nature of roles, not just automating tasks,” Anurag Malik, partner and India leader for People Consulting at EY India, tells AIM. “As AI systems begin to plan, decide, and act with greater autonomy, organisations will create new roles focused on AI orchestration, model oversight, risk and ethics, and domain-led decision making.”

In HR functions, for instance, AI agents are already screening candidates, mapping skills, predicting attrition, and simulating workforce scenarios. What is changing is who owns the outcome.

“What will grow is the role of the human–AI workforce designer, responsible for redefining roles where humans and AI jointly own outcomes, and the AI talent intelligence lead, who will translate AI insights into workforce decisions leaders can stand behind,” Malik explains.

This shift marks a move away from narrow job descriptions toward fluid roles that combine human judgement with machine intelligence. People are no longer just users of AI systems—they are supervisors, interpreters, and ethical stewards.

The scale of this change is already visible. EY’s Work Reimagined research shows India leads in AI adoption, with 62% of employees already using AI regularly at work. But adoption alone is no longer enough.

RAG Behind Agentic AI

In a Reddit post, a user who recently accepted the role of an AI agentic engineer expressed that he was apprehensive about what the new job would entail, as he has mostly been using RAG systems. RAG, or Retrieval-Augmented Generation systems, go beyond training data to combine LLMs with external data sources to provide more accurate answers.

Other users commented that most AI agentic engineers work across RAG pipelines, multi-agent orchestration, and real-world task integration. While the field is still emerging, they observed that engineers who can connect models to actual business or system logic are likely to be in high demand, making this a strong space for rapid growth.

They explained that the core of the job is wiring agents into real business logic while keeping them reliable. Day-to-day work typically includes defining tools with strict JSON schemas, setting timeouts and retries, maintaining evaluation suites and golden tests for each feature, and tracking latency, cost, and failure modes. 

It also involves shipping ETL pipelines to refresh RAG stores, adding safety filters, fallbacks, and human-in-the-loop workflows. In their experience, tools like LangGraph and Temporal are useful for orchestration and retries, Pinecone for retrieval, and DreamFactory for exposing CRUD APIs over legacy SQL with role-based access control so agents can perform real work. 

This evolution is already creating demand for new capabilities, not just technical skills, but cross-functional ones.

“This is creating demand for new skills such as system supervision, prompt and workflow design, outcome validation, and cross-functional problem-solving,” says Nipun Sharma, CEO, TeamLease Degree Apprenticeship. “The real change is not job loss, but job redesign.”

Organisations that recognise this early are moving faster to align their talent strategies with AI-led operating models. Delay risks creating a mismatch between what AI can do and what people are prepared to manage.

“Organisations that proactively realign roles and build these capabilities will unlock higher productivity and resilience, while those that delay will struggle to integrate AI effectively into everyday work,” Sharma warns.

The idea that AI will eliminate jobs outright is increasingly being challenged by those closest to workforce transformation. 

“Agentic AI is fundamentally rewiring the workforce by shifting work from execution to orchestration,” Sharma observes. “As autonomous systems begin to plan, act, and optimise workflows, human roles are evolving toward oversight, judgement, exception handling, and ethical decision-making.”

Beyond the Tech Shift

The transformation is not limited to IT or digital-native sectors. Sangeeta Gupta, senior VP at Nasscom, says that agentic AI will completely change workforce roles across manufacturing, retail, education, and services in the next two to three years.

“What began as rule-based systems has evolved into agentic AI systems that have the capability to act independently, understand context, make decisions, and continuously learn,” she notes. “We foresee agentic AI as a transformative force that will redefine, not replace, workforce roles across industries.”

As AI agents increasingly handle routine analysis, workflows, and follow-ups, humans will move up the value chain. The near-term impact, she emphasises, is not mass displacement but productivity gains driven by end-to-end process redesign.

“Human accountability remains central, especially in safety-critical and regulated environments, making trust, auditability, and clear escalation frameworks essential,” Gupta remarks.

This reality is reflected in how enterprises are deploying agentic AI today. While experimentation is widespread, full autonomy is rare.

“While 62% of global enterprises are experimenting with AI agents, 77% are deploying them with human-in-the-loop design,” Gupta adds, quoting a KPMG report. “Data governance is foundational, with 68% of enterprises strengthening data management to build scalable, reliable agentic solutions.”

The Upskilling Imperative

As roles change, so must skills. Across sectors, demand is growing for domain fluency, process thinking, data literacy, and the ability to supervise agent-driven systems.

“As AI matures, specialised talent demand is expected to rise in areas like advanced AI research, data science, human–technology interface design, and domain-led innovation,” Gupta says.

Nasscom, she adds, is working with government bodies, regulators, and educational institutions to modernise curricula and scale AI literacy. “Industry today is leading by example—accelerating AI and hybrid cloud adoption through reskilling, co-creation, and ecosystem partnerships.”

The message is clear: agentic AI is not replacing human work, but acting as a catalyst to redefine it. The organisations that succeed will be those that redesign roles, invest in reskilling, and build governance frameworks that keep humans firmly in the loop.

As Gupta sums up, “Together, these frameworks support a smooth, human-centred transition where AI agents augment human capabilities without undermining safety, fairness, or societal values.”

The post How Agentic AI is Redesigning Job Roles for Engineers appeared first on Analytics India Magazine.

Generated by RSStT. The copyright belongs to the original author.

Source