Hiring.Camp

Manager - AI/ML (Hybrid)

RTX

·

Today

Location
IN-KA-BENGALURU-NORTHGATE ~ Sy No 2/2 Venkatala Village ~ SY NO 2/2 VENKATALA VILLAGE, Yelahanka Hobli, India
Workplace
Hybrid
Type
Full-time
Seniority
Manager
Closing date
Today
Source
Workday

Description

Date Posted:

2026-09-18

Country:

India

Location:

IN-KA-BENGALURU-NORTHGATE ~ Sy No 2/2 Venkatala Village ~ SY NO 2/2 VENKATALA VILLAGE, Yelahanka Hobli

Position Role Type:

Hybrid

At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world.

Collins Aerospace is a leader in technologically advanced, intelligent solutions that help redefine the aerospace and defense industry. With a comprehensive portfolio and deep technical expertise, we help customers meet the demands of the global market. Join us and help shape the future of aerospace and defense.

What You Will Do *


Our Business Units bring us hard engineering problems — design cycles that take too long, certification evidence that is assembled by hand, simulation campaigns that cannot be run exhaustively, decades of legacy documentation nobody can search. The Applied Research & Technology (ART) organization exists to find out, quickly and honestly, which of those problems AI can actually solve.

As an Engineering Manager you will lead one such team within the ART organization. You will run a portfolio of AI proof of concepts (PoCs) against BU-sponsored problems, prove or disprove value fast, and then make the call that matters most: hand the successful PoC to a central organization such as Digital Technologies (DT) to scale it into a deployable product at a Collins level. Leaving out the ones that do not work is as much a part of the job as scaling the ones that do.


What You Will Own


1. Lead the team
Line-manage and grow a team of 15–20 engineers spanning AI/ML engineering, software engineering, data engineering and domain-facing solution engineers, typically organized into 3–4 pods.
Set technical direction, allocate people across concurrent PoCs, and protect focus when demand exceeds capacity.
Own hiring, onboarding, performance management, career development and retention for the team.
Build a culture where a disproven hypothesis delivered in six weeks is treated as a good outcome, not a failure.


2. Run the PoC portfolio
Operate a structured intake process with Business Units: qualify incoming problems, challenge the framing, and convert vague asks into testable hypotheses with agreed success criteria before any code is written.
Run PoCs on short, time-boxed cycles (typically 8–12 weeks) with stage gates, explicit kill criteria and a named BU sponsor for each.
Maintain a live portfolio view — what is in flight, what it costs, what it is expected to return, and what has been stopped and why.
Ensure every PoC produces a defensible evaluation: baseline comparison, measured performance against BU-relevant metrics, failure mode analysis, and an honest statement of what was not tested.


3. Decide and execute the path after PoC
Own the transition recommendation for each successful PoC, backed by a written assessment of production readiness, data dependencies, integration surface, run cost and ownership model.

Transition to DT or another central organization: package the PoC for handover — architecture documentation, model cards, evaluation results, data lineage, known limitations, backlog — and stay engaged through a defined support period so the receiving team is not left holding an artefact they cannot maintain.
Scale in-house: where the capability is differentiating or too domain-specific to hand over, stand up the engineering to take it to deployment — CI/CD, MLOps, monitoring, model lifecycle management, user support and a funded product roadmap.

Negotiate ownership, funding and SLA boundaries with DT & BU engineering leadership so that transitions are agreements rather than escalations.


4. Technical governance and AI assurance
Set engineering standards for the team: code quality, reproducibility, experiment tracking, data handling, evaluation rigour and documentation.
Ensure AI usage in engineering workflows respects the assurance obligations of a safety-critical environment — traceability of AI-generated or AI-assisted artefacts, human-in-the-loop controls, and alignment with applicable process standards (e.g. DO-178C, ARP4754A) and emerging regulatory guidance (e.g. EASA AI roadmap, EU AI Act) where PoCs touch certification-relevant work.
Work with export control, information security, legal and IP functions on data classification, model and tool selection, and third-party/vendor risk.

5. Represent the team
Act as the primary interface to BU engineering leadership; translate between engineering domain language and AI capability without overselling either.
Report portfolio status, spend and realised benefit to R&T and BU leadership.
Build an external view of the field — vendors, open source, academia, industry consortia — and feed it back into what the team chooses to build versus buy.

Qualifications You Must Have *


10+ years in software, data or AI engineering, including 4+ years managing engineers, with experience managing managers or pod/tech leads at a team size of 15 or above.
Demonstrated delivery of AI/ML systems into production — not only prototypes. You can describe something you shipped, what broke, and what it cost to run.

Hands-on technical depth sufficient to review architecture and challenge your team's approach: modern ML and LLM-based systems, RAG and agentic patterns, evaluation methodology, MLOps and cloud deployment.
Track record of working directly with engineering domain users (design, analysis, test, manufacturing, certification) and turning their problems into working tools they actually adopt.
Experience operating in a stage-gated research or innovation portfolio, including making and defending stop/continue decisions.
Proven ability to hand over or scale a capability across organizational boundaries, with the stakeholder management that requires.

Qualifications We Prefer


Aerospace, defence, automotive or another regulated, safety-critical engineering domain.
Familiarity with the mechanical engineering toolchain — CAD, FEA/CFD, simulation, PLM, requirements management — and where AI genuinely helps in it.
Exposure to AI assurance, explainability, or neuro-symbolic and hybrid approaches for high-integrity contexts.
Experience with both cloud and edge/on-premise deployment, including constrained or disconnected environments.
Background in the engineering discipline the team serves (mechanical, systems, aerospace) alongside the software career.
Prior experience building a function from a small team to a scaled one.


How you work


Honest about uncertainty. You distinguish between what the PoC proved, what it suggested, and what it did not test — to your team and to the sponsor.
Decisive under ambiguity. You will not have complete data before a transition decision is due.
Adoption-focused. A tool nobody uses is not a delivery.
Credible with engineers. You earn technical respect from a senior team without doing their work for them.


What success looks like


First 3 months — Team, portfolio and BU relationships mapped. Intake and stage-gate process defined and agreed with sponsors. A clear view of which in-flight PoCs should continue.
First 6 months — Portfolio running to cadence with measurable throughput. At least one PoC concluded with a documented transition or scale recommendation accepted by leadership. Team structure and hiring plan in place.
First 12 months — At least one capability successfully transitioned to DT or deployed in-house and in real use by a BU. A repeatable PoC-to-production pathway that other teams reference. Demonstrable, quantified engineering benefit attributed to the team's work.

Collins Aerospace, a Raytheon Technologies company, is a leader in technologically advanced and intelligent solutions for the global aerospace and defense industry. Collins Aerospace has the capabilities, comprehensive portfolio and expertise to solve customers’ toughest challenges and to meet the demands of a rapidly evolving global market.

We make modern flight possible for millions of travelers and our military every second.  Our major product lines are on-board virtually every aircraft flying. Be it keeping passengers safe with our emergency power generation systems or creating a positive in-flight experience through reliable cabin pressure controls and quieter engines, Power & Controls focuses on delivering a best-in-class experience to our customers. We hire the top people in the industry. Their ideas drive our performance, and their integrity keeps our customers happy. Join us as we take flight!

WE ARE REDEFINING AEROSPACE. 

*Please consider the following role type definitions as you apply for this role.

Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products.

Hybrid: Employees who are working in Hybrid roles will work regularly both onsite and offsite.  Ratio of time working onsite will be determined in partnership with your leader.

Remote: Employees who are working in Remote roles will work primarily offsite (from home).  An employee may be expected to travel to the site location as needed. 

Regardless of your role type, collaboration and innovation are critical to our business and all employees will have access to digital tools so they can work with colleagues around the world – and access to Collins sites when their work requires in-person meetings.

Some of our competitive benefits package includes:

Benefits package includes:

-         Transportation facility.

-         Group Term Life Insurance.

-         Group Health Insurance.

-         Group Personal Accident Insurance.

-         Entitled for 18 days of vacation and 12 days of contingency leave annually.

-         Employee scholar program.

-         Work life balance.

-         Car lease program.

-         National Pension Scheme

-         LTA

-         Fuel & Maintenance /Driver wages

Nothing matters more to Collins Aerospace than our strong ethical and safety commitments. As such, all India positions require a background check, which may include a drug screen.

Note:

  • Background check required (every external new hire in the India)

  • Drug Screen only performed for Operations Positions

At Collins, the paths we pave together lead to limitless possibility. And the bonds we form – with our customers and with each other -- propel us all higher, again and again.

         

Apply now and be part of the team that’s redefining aerospace, every day.

RTX adheres to the principles of equal employment. All qualified applications will be given careful consideration without regard to ethnicity, color, religion, gender, sexual orientation or identity, national origin, age, disability, protected veteran status or any other characteristic protected by law.  

Privacy Policy and Terms:

Click on this link to read the Policy and Terms

Skills

CI/CDData Engineering

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